Unconventional Fusion and Braiding of Topological Defects in a Lattice Model

We demonstrate the semiclassical nature of symmetry twist defects that differ from quantum deconfined anyons in a true topological phase by examining non-abelian crystalline defects in an abelian lattice model. An underlying non-dynamical ungauged S3-symmetry labels the quasi-extensive defects by group elements and gives rise to order dependent fusion. A central subgroup of local Wilson observables distinguishes defect-anyon composites by species, which can mutate through abelian anyon tunneling by tuning local defect phase parameters. We compute a complete consistent set of primitive basis transformations, or F-symbols, and study braiding and exchange between commuting defects. This suggests a modified spin-statistics theorem for defects and non-modular group structures unitarily represented by the braiding S and exchange T matrices. Non-abelian braiding operations in a closed system represent the sphere braid group projectively by a non-trivial central extension that relates the underlying symmetry.Comment: 44 pages, 43 figure

Stochastic Spin-Orbit Torque Devices as Elements for Bayesian Inference

Probabilistic inference from real-time input data is becoming increasingly popular and may be one of the potential pathways at enabling cognitive intelligence. As a matter of fact, preliminary research has revealed that stochastic functionalities also underlie the spiking behavior of neurons in cortical microcircuits of the human brain. In tune with such observations, neuromorphic and other unconventional computing platforms have recently started adopting the usage of computational units that generate outputs probabilistically, depending on the magnitude of the input stimulus. In this work, we experimentally demonstrate a spintronic device that offers a direct mapping to the functionality of such a controllable stochastic switching element. We show that the probabilistic switching of Ta/CoFeB/MgO heterostructures in presence of spin-orbit torque and thermal noise can be harnessed to enable probabilistic inference in a plethora of unconventional computing scenarios. This work can potentially pave the way for hardware that directly mimics the computational units of Bayesian inference

Freeform Fabrication of Biological Scaffolds by Projection Photopolymerization

This article presents a micro-manufacturing method for direct, projection printing of 3- dimensional (3D) scaffolds for applications in the field of tissue engineering by using a digital micro-mirror-array device (DMD) in a layer-by-layer process. Multi-layered scaffolds are microfabricated using curable materials through an ultraviolet (UV) photopolymerization process. The pre-patterned UV light is projected onto the photocurable polymer solution by creating the “photomask” design with graphic software. Poly (ethylene glycol) diacrylate (PEGDA), is mixed with a small amount of dye (0.3 wt %) to enhance the fabrication resolution of the scaffold. The DMD fabrication system is equipped with a purging mechanism to prevent the accumulation of oligomer, which could interfere with the feature resolution of previously polymerized layers. The surfaces of the pre-designed, multi-layered scaffold are covalently conjugated with fibronectin for efficient cellular attachment. Our results show that murine marrow-derived progenitor cells successfully attached to fibronectin-modified scaffolds.Mechanical Engineerin

Brain Tumor Synthetic Segmentation in 3D Multimodal MRI Scans

The magnetic resonance (MR) analysis of brain tumors is widely used for diagnosis and examination of tumor subregions. The overlapping area among the intensity distribution of healthy, enhancing, non-enhancing, and edema regions makes the automatic segmentation a challenging task. Here, we show that a convolutional neural network trained on high-contrast images can transform the intensity distribution of brain lesions in its internal subregions. Specifically, a generative adversarial network (GAN) is extended to synthesize high-contrast images. A comparison of these synthetic images and real images of brain tumor tissue in MR scans showed significant segmentation improvement and decreased the number of real channels for segmentation. The synthetic images are used as a substitute for real channels and can bypass real modalities in the multimodal brain tumor segmentation framework. Segmentation results on BraTS 2019 dataset demonstrate that our proposed approach can efficiently segment the tumor areas. In the end, we predict patient survival time based on volumetric features of the tumor subregions as well as the age of each case through several regression models

SLIQ: Simple Linear Inequalities for Efficient Contig Scaffolding

Scaffolding is an important subproblem in "de novo" genome assembly in which mate pair data are used to construct a linear sequence of contigs separated by gaps. Here we present SLIQ, a set of simple linear inequalities derived from the geometry of contigs on the line that can be used to predict the relative positions and orientations of contigs from individual mate pair reads and thus produce a contig digraph. The SLIQ inequalities can also filter out unreliable mate pairs and can be used as a preprocessing step for any scaffolding algorithm. We tested the SLIQ inequalities on five real data sets ranging in complexity from simple bacterial genomes to complex mammalian genomes and compared the results to the majority voting procedure used by many other scaffolding algorithms. SLIQ predicted the relative positions and orientations of the contigs with high accuracy in all cases and gave more accurate position predictions than majority voting for complex genomes, in particular the human genome. Finally, we present a simple scaffolding algorithm that produces linear scaffolds given a contig digraph. We show that our algorithm is very efficient compared to other scaffolding algorithms while maintaining high accuracy in predicting both contig positions and orientations for real data sets.Comment: 16 pages, 6 figures, 7 table

Inflation from String/M-Theory Compactification?

We present some exact scalar potentials for the dimensionally reduced theory and examine the possibility of obtaining accelerating 4d cosmology from String/M-theory, more generally, hyperbolic and flux compactification. In the hyperbolic case, even in the zero-flux limit, the scalar potential is positive for the 4d effective theory as required to get an accelerating universe, and thereby evading the ``no-go theorem'' given for static internal space. When we turn on the gauge fields as source terms at the cosmological background with potential V\propto exp(-2c\phi), we find eternally accelerating cosmologies when the 4d space-time is flat and c\geq 1, or hyperbolic and 1<c<\sqrt{2}.Comment: 3 pp. espcrc2.sty. Minor typos corrected and Ref. added. To appear in proceedings of Lattice 2003 (Gravity), Tsukuba, Japan, July 200