Playing Lottery Tickets in Style Transfer Models

Style transfer has achieved great success and attracted a wide range of attention from both academic and industrial communities due to its flexible application scenarios. However, the dependence on a pretty large VGG-based autoencoder leads to existing style transfer models having high parameter complexities, which limits their applications on resource-constrained devices. Compared with many other tasks, the compression of style transfer models has been less explored. Recently, the lottery ticket hypothesis (LTH) has shown great potential in finding extremely sparse matching subnetworks which can achieve on par or even better performance than the original full networks when trained in isolation. In this work, we for the first time perform an empirical study to verify whether such trainable matching subnetworks also exist in style transfer models. Specifically, we take two most popular style transfer models, i.e., AdaIN and SANet, as the main testbeds, which represent global and local transformation based style transfer methods respectively. We carry out extensive experiments and comprehensive analysis, and draw the following conclusions. (1) Compared with fixing the VGG encoder, style transfer models can benefit more from training the whole network together. (2) Using iterative magnitude pruning, we find the matching subnetworks at 89.2% sparsity in AdaIN and 73.7% sparsity in SANet, which demonstrates that style transfer models can play lottery tickets too. (3) The feature transformation module should also be pruned to obtain a much sparser model without affecting the existence and quality of the matching subnetworks. (4) Besides AdaIN and SANet, other models such as LST, MANet, AdaAttN and MCCNet can also play lottery tickets, which shows that LTH can be generalized to various style transfer models

Effects of After-School Programs on Student Cognitive and Non-Cognitive Abilities: A Meta-Analysis Based on 37 Experimental and Quasi-Experimental Studies

The after-school program is a crucial initiative for implementing the Double Reduction policy; however, prior research has not provided conclusive evidence on whether extended school hours contribute to students’ cognitive and non-cognitive development or on which types of after-school services are more beneficial for student development. This study analyzed 37 after-school programs from 18 publications using meta-analytic techniques, and the results indicated that participation in after-school programs had positive effects on student cognitive and non-cognitive development despite the small effect size (d = 0.327, p = 0.000). The decomposition of the effects of after-school programs revealed that they had modestly positive effects on academic achievement (d = 0.369) and social-emotional competence (d = 0.220). In addition, the analysis of moderating variables revealed that socioeconomic status, educational phase, number of after-school service days per week, sample size, and testing instrument all influenced the after-school program effects. This study concludes, based on the results of the meta-analysis, that there should be a balanced consideration of the development of student cognitive and non-cognitive abilities in planning after-school service, a substantial variety of activities in after-school programs, a flexible adoption of diverse after-school programs, and a reasonable participation frequency in after-school service

Magnetic properties of undoped Cu2O fine powders with magnetic impurities and/or cation vacancies

Fine powders of micron- and submicron-sized particles of undoped Cu2O semiconductor, with three different sizes and morphologies have been synthesized by different chemical processes. These samples include nanospheres 200 nm in diameter, octahedra of size 1 micron, and polyhedra of size 800 nm. They exhibit a wide spectrum of magnetic properties. At low temperature, T = 5 K, the octahedron sample is diamagnetic. The nanosphere is paramagnetic. The other two polyhedron samples synthesized in different runs by the same process are found to show different magnetic properties. One of them exhibits weak ferromagnetism with T_C = 455 K and saturation magnetization, M_S = 0.19 emu/g at T = 5 K, while the other is paramagnetic. The total magnetic moment estimated from the detected impurity concentration of Fe, Co, and Ni, is too small to account for the observed magnetism by one to two orders of magnitude. Calculations by the density functional theory (DFT) reveal that cation vacancies in the Cu2O lattice are one of the possible causes of induced magnetic moments. The results further predict that the defect-induced magnetic moments favour a ferromagnetically coupled ground state if the local concentration of cation vacancies, n_C, exceeds 12.5%. This offers a possible scenario to explain the observed magnetic properties. The limitations of the investigations in the present work, in particular in the theoretical calculations, are discussed and possible areas for further study are suggested.Comment: 20 pages, 5 figures 2 tables, submitted to J Phys Condense Matte

Diethyl 2-tert-butyl-6,9-dibromo-4,11-dioxo-5,10-dihydro-cis-1H,3H,4H,11H-2-azo-3a,4a,10a,11a-tetra­aza­benz[f]indeno[2,1,7-ija]azulene-11b,11c-dicarboxyl­ate

In the title compound, C24H29Br2N5O6, a glycoluril derivative, the 1,4-dibromo­benzene ring is fused to the seven-membered ring of the glycoluril unit containing two N atoms. The two five-membered rings in the glycoluril unit are approximately planar and the dihedral angle between them is 69.8 (2)°. The six-membered ring containing three N atoms adopts a chair conformation. The crystal packing is stabilized by an inter­molecular non-classical C—H⋯O hydrogen bond and a weak C—H⋯π inter­action. Both of the ester groups are found to be disordered over two positions. The occupancies of the disordered positions were refined to 0.73(1):0.27(1) and 0.56(1):0.44(1)

Crowd3D: Towards Hundreds of People Reconstruction from a Single Image

Image-based multi-person reconstruction in wide-field large scenes is critical for crowd analysis and security alert. However, existing methods cannot deal with large scenes containing hundreds of people, which encounter the challenges of large number of people, large variations in human scale, and complex spatial distribution. In this paper, we propose Crowd3D, the first framework to reconstruct the 3D poses, shapes and locations of hundreds of people with global consistency from a single large-scene image. The core of our approach is to convert the problem of complex crowd localization into pixel localization with the help of our newly defined concept, Human-scene Virtual Interaction Point (HVIP). To reconstruct the crowd with global consistency, we propose a progressive reconstruction network based on HVIP by pre-estimating a scene-level camera and a ground plane. To deal with a large number of persons and various human sizes, we also design an adaptive human-centric cropping scheme. Besides, we contribute a benchmark dataset, LargeCrowd, for crowd reconstruction in a large scene. Experimental results demonstrate the effectiveness of the proposed method. The code and datasets will be made public.Comment: 8 pages (not including reference

The Bromodomain and Extra-Terminal Protein Inhibitor OTX015 Suppresses T Helper Cell Proliferation and Differentiation

BACKGROUND: Dynamic epigenetic alterations accompanying CD4+ T helper cell differentiation have been implicated in multiple autoimmune diseases. The bromodomain and extra-terminal (BET) proteins are epigenetic regulators that recognize and bind to acetylated histones in chromatin and are targets for pharmacological inhibition. In this study we tested a new BET inhibitor under clinical development, OTX015, to interrogate its effects on key CD4+ T cell subsets associated with autoimmunity. METHODS: Naïve and memory murine and human CD4+ T cells were isolated and differentiated into populations characterized by the expression of interferon (IFN)-γ and interleukin (IL)-17. Cultured cells were then exposed to varying concentrations of OTX015 in vitro, and its impact on cytokine expression was quantified by flow cytometry. In parallel, the expression of the transcription factors TBX21 and RORC was quantified by PCR. A previously studied BET inhibitor JQ1 was used as a pharmacological control. RESULTS: OTX015 suppressed both murine and human CD4+ T cell proliferation. Its impact on cytokine expression varied in murine and human naïve and memory subsets. OTX015 was similarly effective as JQ1 in the suppression of cytokines and T helper cell proliferation. Higher concentrations of OTX015 also had a greater impact on the viability of murine versus human cells. IL-17 and IFN-γ expression was not altered in murine memory CD4+ T cells, whereas in human memory CD4+ T cells, OTX015 inhibited IL-17, but not IFN-γ. Across all human T cell subsets OTX015 suppressed IL-17 more effectively than IFN-γ. CONCLUSION: Our studies demonstrate that OTX015 has anti-inflammatory effects by suppressing murine and human CD4+ T cell proliferation and subset-dependent proinflammatory cytokine expression, including the selective suppression of IL-17 in human memory CD4+ T cells

Playing lottery tickets in style transfer models

Style transfer has achieved great success and attracted a wide range of attention from both academic and industrial communities due to its flexible application scenarios. However, the dependence on a pretty large VGG-based autoencoder leads to existing style transfer models having high parameter complexities, which limits their applications on resource-constrained devices. Compared with many other tasks, the compression of style transfer models has been less explored. Recently, the lottery ticket hypothesis (LTH) has shown great potential in finding extremely sparse matching subnetworks which can achieve on par or even better performance than the original full networks when trained in isolation. In this work, we for the first time perform an empirical study to verify whether such trainable matching subnetworks also exist in style transfer models. Specifically, we take two most popular style transfer models, i.e., AdaIN and SANet, as the main testbeds, which represent global and local transformation based style transfer methods respectively. We carry out extensive experiments and comprehensive analysis, and draw the following conclusions. (1) Compared with fixing the VGG encoder, style transfer models can benefit more from training the whole network together. (2) Using iterative magnitude pruning, we find the matching subnetworks at 89.2% sparsity in AdaIN and 73.7% sparsity in SANet, which demonstrates that Style transfer models can play lottery tickets too. (3) The feature transformation module should also be pruned to obtain a much sparser model without affecting the existence and quality of the matching subnetworks. (4) Besides AdaIN and SANet, other models such as LST, MANet, AdaAttN and MCCNet can also play lottery tickets, which shows that LTH can be generalized to various style transfer models

Activity-assisted barrier-crossing of self-propelled colloids over parallel microgrooves

We report a systematic study of the dynamics of self-propelled particles (SPPs) over a one-dimensional periodic potential landscape, which is fabricated on a microgroove-patterned polydimethylsiloxane (PDMS) substrate. From the measured non-equilibrium probability density function of the SPPs, we find that the escape dynamics of the slow-rotating SPPs across the potential landscape can be described by an effective potential, once the self-propulsion force is included into the potential under the fixed angle approximation. This work demonstrates that the parallel microgrooves provide a versatile platform for a quantitative understanding of the interplay among the self-propulsion force, spatial confinement by the potential landscape, and thermal noise, as well as its effects on activity-assisted escape dynamics and transport of the SPPs