Grouping-matrix based Graph Pooling with Adaptive Number of Clusters

Graph pooling is a crucial operation for encoding hierarchical structures within graphs. Most existing graph pooling approaches formulate the problem as a node clustering task which effectively captures the graph topology. Conventional methods ask users to specify an appropriate number of clusters as a hyperparameter, then assume that all input graphs share the same number of clusters. In inductive settings where the number of clusters can vary, however, the model should be able to represent this variation in its pooling layers in order to learn suitable clusters. Thus we propose GMPool, a novel differentiable graph pooling architecture that automatically determines the appropriate number of clusters based on the input data. The main intuition involves a grouping matrix defined as a quadratic form of the pooling operator, which induces use of binary classification probabilities of pairwise combinations of nodes. GMPool obtains the pooling operator by first computing the grouping matrix, then decomposing it. Extensive evaluations on molecular property prediction tasks demonstrate that our method outperforms conventional methods.Comment: 10 pages, 3 figure

Geometrically Aligned Transfer Encoder for Inductive Transfer in Regression Tasks

Transfer learning is a crucial technique for handling a small amount of data that is potentially related to other abundant data. However, most of the existing methods are focused on classification tasks using images and language datasets. Therefore, in order to expand the transfer learning scheme to regression tasks, we propose a novel transfer technique based on differential geometry, namely the Geometrically Aligned Transfer Encoder (GATE). In this method, we interpret the latent vectors from the model to exist on a Riemannian curved manifold. We find a proper diffeomorphism between pairs of tasks to ensure that every arbitrary point maps to a locally flat coordinate in the overlapping region, allowing the transfer of knowledge from the source to the target data. This also serves as an effective regularizer for the model to behave in extrapolation regions. In this article, we demonstrate that GATE outperforms conventional methods and exhibits stable behavior in both the latent space and extrapolation regions for various molecular graph datasets.Comment: 12+11 pages, 6+1 figures, 0+7 table

3D Denoisers are Good 2D Teachers: Molecular Pretraining via Denoising and Cross-Modal Distillation

Pretraining molecular representations from large unlabeled data is essential for molecular property prediction due to the high cost of obtaining ground-truth labels. While there exist various 2D graph-based molecular pretraining approaches, these methods struggle to show statistically significant gains in predictive performance. Recent work have thus instead proposed 3D conformer-based pretraining under the task of denoising, which led to promising results. During downstream finetuning, however, models trained with 3D conformers require accurate atom-coordinates of previously unseen molecules, which are computationally expensive to acquire at scale. In light of this limitation, we propose D&D, a self-supervised molecular representation learning framework that pretrains a 2D graph encoder by distilling representations from a 3D denoiser. With denoising followed by cross-modal knowledge distillation, our approach enjoys use of knowledge obtained from denoising as well as painless application to downstream tasks with no access to accurate conformers. Experiments on real-world molecular property prediction datasets show that the graph encoder trained via D&D can infer 3D information based on the 2D graph and shows superior performance and label-efficiency against other baselines.Comment: 16 pages, 5 figure

Stimulated penetrating keratoplasty using real-time virtual intraoperative surgical optical coherence tomography

An intraoperative surgical microscope is an essential tool in a neuro-or ophthalmological surgical environment. Yet, it has an inherent limitation to classify subsurface information because it only provides the surface images. To compensate for and assist in this problem, combining the surgical microscope with optical coherence tomography (OCT) has been adapted. We developed a real-time virtual intraoperative surgical OCT (VISOCT) system by adapting a spectral-domain OCT scanner with a commercial surgical microscope. Thanks to our custommade beam splitting and image display subsystems, the OCT images and microscopic images are simultaneously visualized through an ocular lens or the eyepiece of the microscope. This improvement helps surgeons to focus on the operation without distraction to view OCT images on another separate display. Moreover, displaying the OCT live images on the eyepiece helps surgeon's depth perception during the surgeries. Finally, we successfully processed stimulated penetrating keratoplasty in live rabbits. We believe that these technical achievements are crucial to enhance the usability of the VISOCT system in a real surgical operating condition.open0

Promoting Thermal Conductivity of Alumina-Based Composite Materials by Systematically Incorporating Modified Graphene Oxide

Small amounts of thermally conductive graphene oxide (GO) and modified GO are systematically introduced as a second filler to thermal interface materials (TIMs) consisting of alumina (Al2O3) particles and polydimethylsiloxane (PDMS). The surface of GO is covalently linked with an organic moiety, octadecylamine (ODA), to significantly improve the miscibility and dispersity of GO across the TIM matrix. Subsequently, two series of PDMS-Al2O3 composite TIMs are manufactured as a function of GO and ODA-GO content (0.25 wt%–2.5 wt%) to understand the effect of these second additives. The incorporation of GO into the Al2O3-PDMS composite materials generally increases the thermal conductivity (TC), ranging from 18% to 29%. Conversely, the use of ODA-GO further enhances the overall performance of TIMs (22–54%) by facilitating the dispersion degree of GO across the composite matrix. The great improvement in TC is presumably related to the formation of conductive pathways by uniformly integrating 2D-type GO flakes across spherical Al2O3 particle networks. The ability to simply regulate the polarity of the thermally conductive second filler can provide an idea for designing cost-effective and practical TIM-2-type pads that can be commercially applicable in between an integrated heat spreader and a heat sink

MYC and BCL2 overexpression is associated with a higher class of Memorial Sloan-Kettering Cancer Center prognostic model and poor clinical outcome in primary diffuse large B-cell lymphoma of the central nervous system

Table S1. Correlation of BCL6 expression and clinicopathological variables; Table S2. MYC translocation and copy number change in MYC positive cases. (DOCX 24 kb

Recent Advances in Vertically Aligned Nanowires for Photonics Applications

Over the past few decades, nanowires have arisen as a centerpiece in various fields of application from electronics to photonics, and, recently, even in bio-devices. Vertically aligned nanowires are a particularly decent example of commercially manufacturable nanostructures with regard to its packing fraction and matured fabrication techniques, which is promising for mass-production and low fabrication cost. Here, we track recent advances in vertically aligned nanowires focused in the area of photonics applications. Begin with the core optical properties in nanowires, this review mainly highlights the photonics applications such as light-emitting diodes, lasers, spectral filters, structural coloration and artificial retina using vertically aligned nanowires with the essential fabrication methods based on top-down and bottom-up approaches. Finally, the remaining challenges will be briefly discussed to provide future directions

Simultaneous imaging using combined optical coherence tomography (OCT) and photoacoustic microscopy (PAM)

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Two-axis polydimethylsiloxane-based electromagnetic microelectromechanical system scanning mirror for optical coherence tomography

Compact size and fast imaging abilities are key requirements for the clinical implementation of an optical coherence tomography (OCT) system. Among the various small-sized technology, a microelectromechanical system (MEMS) scanning mirror is widely used in a miniaturized OCT system. However, the complexities of conventional MEMS fabrication processes and relatively high costs have restricted fast clinical translation and commercialization of the OCT systems. To resolve these problems, we developed a two-axis polydimethylsiloxane (PDMS)-based MEMS (2A-PDMS-MEMS) scanning mirror through simple processes with low costs. It had a small size of 15 x 15 x 15 mm(3), was fast, and had a wide scanning range at a low voltage. The AC/ DC responses were measured to evaluate the performance of the 2A-PDMS-MEMS scanning mirror. The maximum scanning angles were measured as +/- 16.6 deg and +/- 11.6 deg along the X and Y axes, respectively, and the corresponding field of view was 29.8 mm x 20.5 mm with an optical focal length of 50 mm. The resonance frequencies were 82 and 57 Hz along the X and Y axes, respectively. Finally, in vivo B-scan and volumetric OCT images of human fingertips and palms were successfully acquired using the developed SD-OCT system based on the 2A-PDMS-MEMS scanning mirror. (C) 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)111Nsciescopu