Laser powder bed fusion of a superelastic Cu-Al-Mn shape memory alloy

Dense and crack-free specimens of the shape memory alloy Cu71.6Al17Mn11.4 (at.%) were produced via laser powder bed fusion across a wide range of process parameters. The microstructure, viz. grain size, can be directly tailored within the process and with it the transformation temperatures (TTs) shifted to higher values by raising the energy input. The microstructure, and the superelastic behavior of additively manufactured samples were assessed by a detailed comparison with induction melted material. The precipitation of the α phase, which inhibit the martensitic transformation, were not observed in the additively manufactured samples owing to the high intrinsic cooling rates during the fabrication process. Fine columnar grains with a strong [001]-texture along the building direction lead to an enhanced yield strength compared to the coarse-grained cast samples. A maximum recoverable strain of 2.86% was observed after 5% compressive loading. The first results of our approach imply that laser powder bed fusion is a promising technique to directly produce individually designed Cu-Al-Mn shape memory parts with a pronounced superelasticity at room temperature

Effects of rapid maxillary expansion on nasal mucociliary clearance

Objective: To evaluate the changes in nasal mucociliary clearance in orthodontic patients after rapid maxillary expansion (RME) therapy. Materials and Methods: Forty-two children (25 boys and 17 girls) participated in this study. The RME group consisted of 21 patients (mean age, 13.8 years), who had undergone RME at the initiation of orthodontic treatment. The control group consisted of 21 subjects (mean age, 13.6 years), who were attending the department of orthodontics for active orthodontic treatment. The nasal mucociliary clearance was assessed by the saccharin test. Saccharin transit times (STTs) were measured for each treated subject before expansion (T1), after RME (T2), and after a 3-month retention period (T3). Records were obtained at the same time intervals for each group. Results: The STT decreased significantly in the RME group after expansion and retention (P <.05). A statistically significant difference was found when the STTs of the control and RME groups were compared after expansion and retention (P <.05). Conclusions: The STTs of young orthodontic patients with maxillary narrowness and without any history of nasal or systemic disease were within normal limits. However, RME increased the mucociliary clearance in patients who had maxillary narrowness, having positive effects on nasal physiology and increasing nasal cavity volume. © 2016 by The EH Angle Education and Research Foundation, Inc

Motion Deblurring in the Wild

The task of image deblurring is a very ill-posed problem as both the image and the blur are unknown. Moreover, when pictures are taken in the wild, this task becomes even more challenging due to the blur varying spatially and the occlusions between the object. Due to the complexity of the general image model we propose a novel convolutional network architecture which directly generates the sharp image.This network is built in three stages, and exploits the benefits of pyramid schemes often used in blind deconvolution. One of the main difficulties in training such a network is to design a suitable dataset. While useful data can be obtained by synthetically blurring a collection of images, more realistic data must be collected in the wild. To obtain such data we use a high frame rate video camera and keep one frame as the sharp image and frame average as the corresponding blurred image. We show that this realistic dataset is key in achieving state-of-the-art performance and dealing with occlusions

The Effect of the Pairing Interaction on the Energies of Isobar Analog Resonances in 112−124^{112-124}Sb and Isospin Admixture in 100−124^{100-124}Sn Isotopes

In the present study, the effect of the pairing interaction and the isovector correlation between nucleons on the properties of the isobar analog resonances (IAR) in $^{112-124}$Sb isotopes and the isospin admixture in $^{100-124}$Sn isotopes is investigated within the framework of the quasiparticle random phase approximation (QRPA). The form of the interaction strength parameter is related to the shell model potential by restoring the isotopic invariance of the nuclear part of the total Hamiltonian. In this respect, the isospin admixtures in the $^{100-124}$Sn isotopes are calculated, and the dependence of the differential cross section and the volume integral $J_{F}$ for the Sn($^{3}$He,t)Sb reactions at E($^{3}$He)$=200$ MeV occurring by the excitation of IAR on mass number A is examined. Our results show that the calculated value for the isospin mixing in the $^{100}$Sn isotope is in good agreement with Colo et al.'s estimates $(4-5$, and the obtained values for the volume integral change within the error range of the value reported by Fujiwara et al. (53$\pm$5 MeV fm$^{3}$). Moreover, it is concluded that although the differential cross section of the isobar analog resonance for the ($^{3}$He,t) reactions is not sensitive to pairing correlations between nucleons, a considerable effect on the isospin admixtures in $N\approx Z$ isotopes can be seen with the presence of these correlations.Comment: 16 pages, 5 EPS figures and 2 tables, Late

Simple, Accurate, and Robust Nonparametric Blind Super-Resolution

This paper proposes a simple, accurate, and robust approach to single image nonparametric blind Super-Resolution (SR). This task is formulated as a functional to be minimized with respect to both an intermediate super-resolved image and a nonparametric blur-kernel. The proposed approach includes a convolution consistency constraint which uses a non-blind learning-based SR result to better guide the estimation process. Another key component is the unnatural bi-l0-l2-norm regularization imposed on the super-resolved, sharp image and the blur-kernel, which is shown to be quite beneficial for estimating the blur-kernel accurately. The numerical optimization is implemented by coupling the splitting augmented Lagrangian and the conjugate gradient (CG). Using the pre-estimated blur-kernel, we finally reconstruct the SR image by a very simple non-blind SR method that uses a natural image prior. The proposed approach is demonstrated to achieve better performance than the recent method by Michaeli and Irani [2] in both terms of the kernel estimation accuracy and image SR quality

Variational Bayesian causal connectivity analysis for fMRI

The ability to accurately estimate effective connectivity among brain regions from neuroimaging data could help answering many open questions in neuroscience. We propose a method which uses causality to obtain a measure of effective connectivity from fMRI data. The method uses a vector autoregressive model for the latent variables describing neuronal activity in combination with a linear observation model based on a convolution with a hemodynamic response function. Due to the employed modeling, it is possible to efficiently estimate all latent variables of the model using a variational Bayesian inference algorithm. The computational efficiency of the method enables us to apply it to large scale problems with high sampling rates and several hundred regions of interest. We use a comprehensive empirical evaluation with synthetic and real fMRI data to evaluate the performance of our method under various conditions.This work was partially supported by the National Institute of Child Health and Human Development (R01 HD042049). Martin Luessi was partially supported by the Swiss National Science Foundation Early Postdoc Mobility fellowship 148485. This work was supported in part by the Department of Energy under Contract DE-NA0000457, the “Ministerio de Ciencia e Innovación” under Contract TIN2010-15137, and the CEI BioTic with the Universidad de Granada Data were provided (in part) by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University

Vector meson production and nucleon resonance analysis in a coupled-channel approach for energies m_N < sqrt(s) < 2 GeV II: photon-induced results

We present a nucleon resonance analysis by simultaneously considering all pion- and photon-induced experimental data on the final states gamma N, pi N, 2 pi N, eta N, K Lambda, K Sigma, and omega N for energies from the nucleon mass up to sqrt(s) = 2 GeV. In this analysis we find strong evidence for the resonances P_{31}(1750), P_{13}(1900), P_{33}(1920), and D_{13}(1950). The omega N production mechanism is dominated by large P_{11}(1710) and P_{13}(1900) contributions. In this second part we present the results on the photoproduction reactions and the electromagnetic properties of the resonances. The inclusion of all important final states up to sqrt(s) = 2 GeV allows for estimates on the importance of the individual states for the GDH sum rule.Comment: 41 pages, 26 figures, discussion extended, typos corrected, references updated, to appear in Phys. Rev.

Visualizing Escherichia coli Sub-Cellular Structure Using Sparse Deconvolution Spatial Light Interference Tomography

Studying the 3D sub-cellular structure of living cells is essential to our understanding of biological function. However, tomographic imaging of live cells is challenging mainly because they are transparent, i.e., weakly scattering structures. Therefore, this type of imaging has been implemented largely using fluorescence techniques. While confocal fluorescence imaging is a common approach to achieve sectioning, it requires fluorescence probes that are often harmful to the living specimen. On the other hand, by using the intrinsic contrast of the structures it is possible to study living cells in a non-invasive manner. One method that provides high-resolution quantitative information about nanoscale structures is a broadband interferometric technique known as Spatial Light Interference Microscopy (SLIM). In addition to rendering quantitative phase information, when combined with a high numerical aperture objective, SLIM also provides excellent depth sectioning capabilities. However, like in all linear optical systems, SLIM's resolution is limited by diffraction. Here we present a novel 3D field deconvolution algorithm that exploits the sparsity of phase images and renders images with resolution beyond the diffraction limit. We employ this label-free method, called deconvolution Spatial Light Interference Tomography (dSLIT), to visualize coiled sub-cellular structures in E. coli cells which are most likely the cytoskeletal MreB protein and the division site regulating MinCDE proteins. Previously these structures have only been observed using specialized strains and plasmids and fluorescence techniques. Our results indicate that dSLIT can be employed to study such structures in a practical and non-invasive manner