Variational Deep Semantic Hashing for Text Documents

As the amount of textual data has been rapidly increasing over the past decade, efficient similarity search methods have become a crucial component of large-scale information retrieval systems. A popular strategy is to represent original data samples by compact binary codes through hashing. A spectrum of machine learning methods have been utilized, but they often lack expressiveness and flexibility in modeling to learn effective representations. The recent advances of deep learning in a wide range of applications has demonstrated its capability to learn robust and powerful feature representations for complex data. Especially, deep generative models naturally combine the expressiveness of probabilistic generative models with the high capacity of deep neural networks, which is very suitable for text modeling. However, little work has leveraged the recent progress in deep learning for text hashing. In this paper, we propose a series of novel deep document generative models for text hashing. The first proposed model is unsupervised while the second one is supervised by utilizing document labels/tags for hashing. The third model further considers document-specific factors that affect the generation of words. The probabilistic generative formulation of the proposed models provides a principled framework for model extension, uncertainty estimation, simulation, and interpretability. Based on variational inference and reparameterization, the proposed models can be interpreted as encoder-decoder deep neural networks and thus they are capable of learning complex nonlinear distributed representations of the original documents. We conduct a comprehensive set of experiments on four public testbeds. The experimental results have demonstrated the effectiveness of the proposed supervised learning models for text hashing.Comment: 11 pages, 4 figure

Fusion of radioactive 132^{132}Sn with 64^{64}Ni

Evaporation residue and fission cross sections of radioactive $^{132}$Sn on $^{64}$Ni were measured near the Coulomb barrier. A large sub-barrier fusion enhancement was observed. Coupled-channel calculations including inelastic excitation of the projectile and target, and neutron transfer are in good agreement with the measured fusion excitation function. When the change in nuclear size and shift in barrier height are accounted for, there is no extra fusion enhancement in $^{132}$Sn+$^{64}$Ni with respect to stable Sn+$^{64}$Ni. A systematic comparison of evaporation residue cross sections for the fusion of even $^{112-124}$Sn and $^{132}$Sn with $^{64}$Ni is presented.Comment: 9 pages, 11 figure

Zero-Shot Hashing via Transferring Supervised Knowledge

Hashing has shown its efficiency and effectiveness in facilitating large-scale multimedia applications. Supervised knowledge e.g. semantic labels or pair-wise relationship) associated to data is capable of significantly improving the quality of hash codes and hash functions. However, confronted with the rapid growth of newly-emerging concepts and multimedia data on the Web, existing supervised hashing approaches may easily suffer from the scarcity and validity of supervised information due to the expensive cost of manual labelling. In this paper, we propose a novel hashing scheme, termed \emph{zero-shot hashing} (ZSH), which compresses images of "unseen" categories to binary codes with hash functions learned from limited training data of "seen" categories. Specifically, we project independent data labels i.e. 0/1-form label vectors) into semantic embedding space, where semantic relationships among all the labels can be precisely characterized and thus seen supervised knowledge can be transferred to unseen classes. Moreover, in order to cope with the semantic shift problem, we rotate the embedded space to more suitably align the embedded semantics with the low-level visual feature space, thereby alleviating the influence of semantic gap. In the meantime, to exert positive effects on learning high-quality hash functions, we further propose to preserve local structural property and discrete nature in binary codes. Besides, we develop an efficient alternating algorithm to solve the ZSH model. Extensive experiments conducted on various real-life datasets show the superior zero-shot image retrieval performance of ZSH as compared to several state-of-the-art hashing methods.Comment: 11 page

3D printing fluorescent material with tunable optical properties

The 3D printing of fluorescent materials could help develop, validate, and translate imaging technologies, including systems for fluorescence-guided surgery. Despite advances in 3D printing techniques for optical targets, no comprehensive method has been demonstrated for the simultaneous incorporation of fluorophores and fine-tuning of absorption and scattering properties. Here, we introduce a photopolymer-based 3D printing method for manufacturing fluorescent material with tunable optical properties. The results demonstrate the ability to 3D print various individual fluorophores at reasonably high fluorescence yields, including IR-125, quantum dots, methylene blue, and rhodamine 590. Furthermore, tuning of the absorption and reduced scattering coefficients is demonstrated within the relevant mamalian soft tissue coefficient ranges of 0.005–0.05 mm−1 and 0.2–1.5 mm−1, respectively. Fabrication of fluorophore-doped biomimicking and complex geometric structures validated the ability to print feature sizes less than 200 μm. The presented methods and optical characterization techniques provide the foundation for the manufacturing of solid 3D printed fluorescent structures, with direct relevance to biomedical optics and the broad adoption of fast manufacturing methods in fluorescence imaging

Phase Decomposition and Chemical Inhomogeneity in Nd2-xCexCuO4

Extensive X-ray and neutron scattering experiments and additional transmission electron microscopy results reveal the partial decomposition of Nd2-xCexCuO4 (NCCO) in a low-oxygen-fugacity environment such as that typically realized during the annealing process required to create a superconducting state. Unlike a typical situation in which a disordered secondary phase results in diffuse powder scattering, a serendipitous match between the in-plane lattice constant of NCCO and the lattice constant of one of the decomposition products, (Nd,Ce)2O3, causes the secondary phase to form an oriented, quasi-two-dimensional epitaxial structure. Consequently, diffraction peaks from the secondary phase appear at rational positions (H,K,0) in the reciprocal space of NCCO. Additionally, because of neodymium paramagnetism, the application of a magnetic field increases the low-temperature intensity observed at these positions via neutron scattering. Such effects may mimic the formation of a structural superlattice or the strengthening of antiferromagnetic order of NCCO, but the intrinsic mechanism may be identified through careful and systematic experimentation. For typical reduction conditions, the (Nd,Ce)2O3 volume fraction is ~1%, and the secondary-phase layers exhibit long-range order parallel to the NCCO CuO2 sheets and are 50-100 angstromsthick. The presence of the secondary phase should also be taken into account in the analysis of other experiments on NCCO, such as transport measurements.Comment: 15 pages, 17 figures, submitted to Phys. Rev.

Fragment Production in Non-central Collisions of Intermediate Energy Heavy Ions

The defining characteristics of fragment emission resulting from the non-central collision of 114Cd ions with 92Mo target nuclei at E/A = 50 MeV are presented. Charge correlations and average relative velocities for mid-velocity fragment emission exhibit significant differences when compared to standard statistical decay. These differences associated with similar velocity dissipation are indicative of the influence of the entrance channel dynamics on the fragment production process

Interplay of initial deformation and Coulomb proximity on nuclear decay

Alpha particles emitted from an excited projectile-like fragment (PLF*) formed in a peripheral collision of two intermediate-energy heavy ions exhibit a strong preference for emission towards the target-like fragment (TLF). The interplay of the initial deformation of the PLF* caused by the reaction, Coulomb proximity, and the rotation of the PLF* results in the observed anisotropic angular distribution. Changes in the shape of the angular distribution with excitation energy are interpreted as being the result of forming more elongated initial geometries in the more peripheral collisions.Comment: 4 figure

Enhanced Fusion-Evaporation Cross Sections in Neutron-Rich 132^{132}Sn on 64^{64}Ni

Evaporation residue cross sections have been measured with neutron-rich radioactive $^{132}$Sn beams on $^{64}$Ni in the vicinity of the Coulomb barrier. The average beam intensity was $2\times 10^{4}$ particles per second and the smallest cross section measured was less than 5 mb. Large subbarrier fusion enhancement was observed. Coupled-channels calculations taking into account inelastic excitation and neutron transfer underpredict the measured cross sections below the barrier.Comment: 4 pages including 1 table and 3 figure