(E)-2-Meth­oxy-N′-(4-nitro­benzyl­idene)benzohydrazide

In the title compound, C15H13N3O4, the mol­ecule exists in a trans configuration with respect to the methyl­idene unit. The dihedral angle between the two benzene rings is 6.8 (2)°. The C—N—NH—C torsion angle is 3.4 (3)°. The mol­ecule possesses an intra­molecular N—H⋯O hydrogen bond. In the crystal structure, adjacent mol­ecules are linked through inter­molecular C—H⋯O hydrogen bonds, forming dimer

Graph Neural Network-Aided Exploratory Learning for Community Detection with Unknown Topology

In social networks, the discovery of community structures has received considerable attention as a fundamental problem in various network analysis tasks. However, due to privacy concerns or access restrictions, the network structure is often unknown, thereby rendering established community detection approaches ineffective without costly network topology acquisition. To tackle this challenge, we present META-CODE, a novel end-to-end solution for detecting overlapping communities in networks with unknown topology via exploratory learning aided by easy-to-collect node metadata. Specifically, META-CODE consists of three iterative steps in addition to the initial network inference step: 1) node-level community-affiliation embeddings based on graph neural networks (GNNs) trained by our new reconstruction loss, 2) network exploration via community affiliation-based node queries, and 3) network inference using an edge connectivity-based Siamese neural network model from the explored network. Through comprehensive evaluations using five real-world datasets, we demonstrate that META-CODE exhibits (a) its superiority over benchmark community detection methods, (b) empirical evaluations as well as theoretical findings to see the effectiveness of our node query, (c) the influence of each module, and (d) its computational efficiency.Comment: 15 pages, 8 figures, 5 tables; its conference version was presented at the ACM International Conference on Information and Knowledge Management (CIKM 2022

FastHiC: a fast and accurate algorithm to detect long-range chromosomal interactions from Hi-C data

Motivation: How chromatin folds in three-dimensional (3D) space is closely related to transcription regulation. As powerful tools to study such 3D chromatin conformation, the recently developed Hi-C technologies enable a genome-wide measurement of pair-wise chromatin interaction. However, methods for the detection of biologically meaningful chromatin interactions, i.e. peak calling, from Hi-C data, are still under development. In our previous work, we have developed a novel hidden Markov random field (HMRF) based Bayesian method, which through explicitly modeling the non-negligible spatial dependency among adjacent pairs of loci manifesting in high resolution Hi-C data, achieves substantially improved robustness and enhanced statistical power in peak calling. Superior to peak callers that ignore spatial dependency both methodologically and in performance, our previous Bayesian framework suffers from heavy computational costs due to intensive computation incurred by modeling the correlated peak status of neighboring loci pairs and the inference of hidden dependency structure

Realization of Zero-Refractive-Index Lens with Ultralow Spherical Aberration

Optical complex materials offer unprecedented opportunity to engineer fundamental band dispersion which enables novel optoelectronic functionality and devices. Exploration of photonic Dirac cone at the center of momentum space has inspired an exceptional characteristic of zero-index, which is similar to zero effective mass in fermionic Dirac systems. Such all-dielectric zero-index photonic crystals provide an in-plane mechanism such that the energy of the propagating waves can be well confined along the chip direction. A straightforward example is to achieve the anomalous focusing effect without longitudinal spherical aberration, when the size of zero-index lens is large enough. Here, we designed and fabricated a prototype of zero-refractive-index lens by comprising large-area silicon nanopillar array with plane-concave profile. Near-zero refractive index was quantitatively measured near 1.55 um through anomalous focusing effect, predictable by effective medium theory. The zero-index lens was also demonstrated to perform ultralow longitudinal spherical aberration. Such IC compatible device provides a new route to integrate all-silicon zero-index materials into optical communication, sensing, and modulation, and to study fundamental physics on the emergent fields of topological photonics and valley photonics.Comment: 14 pages, 4 figure

BGGAN: Bokeh-Glass Generative Adversarial Network for Rendering Realistic Bokeh

A photo captured with bokeh effect often means objects in focus are sharp while the out-of-focus areas are all blurred. DSLR can easily render this kind of effect naturally. However, due to the limitation of sensors, smartphones cannot capture images with depth-of-field effects directly. In this paper, we propose a novel generator called Glass-Net, which generates bokeh images not relying on complex hardware. Meanwhile, the GAN-based method and perceptual loss are combined for rendering a realistic bokeh effect in the stage of finetuning the model. Moreover, Instance Normalization(IN) is reimplemented in our network, which ensures our tflite model with IN can be accelerated on smartphone GPU. Experiments show that our method is able to render a high-quality bokeh effect and process one $1024 \times 1536$ pixel image in 1.9 seconds on all smartphone chipsets. This approach ranked First in AIM 2020 Rendering Realistic Bokeh Challenge Track 1 \& Track 2.Comment: accepted by ECCV workshop 202