A Near-Infrared Study of the Highly-Obscured Active Star-Forming Region W51B

We present wide-field JHKs-band photometric observations of the three compact HII regions G48.9-0.3, G49.0-0.3, and G49.2-0.3 in the active star-forming region W51B. The star clusters inside the three compact HII regions show the excess number of stars in the J-Ks histograms compared with reference fields. While the mean color excess ratio E(J-H)/E(H-Ks) of the three compact HII regions are similar to ~ 2.07, the visual extinctions toward them are somewhat different: ~ 17 mag for G48.9-0.3 and G49.0-0.3; ~ 23 mag for G49.2-0.3. Based on their sizes and brightnesses, we suggest that the age of each compact HII region is =< 2 Myr. The inferred total stellar mass, ~ 1.4 x 10^4 M_sun, of W51B makes it one of the most active star forming regions in the Galaxy with the star formation efficiency of ~ 10 %.Comment: 12 pages, 10 eps figures, uses jkas.st

Numerical modeling to analysis the abrasion of knee joint by walking pattern

In current studies, growing up of treatment of the knee joint damage such as arthritis, the research to prevent knee joint is under way. As knee joints could be damaged by various types of motion, one of the most influential factor of the abrasion on the knee joint is progressed by walking. It could be classified as 3 types of walking, 1. Walking plain, 2. Climbing stairs or uphill and 3. Going down. In this study, to find the damaged point of knee joint, the following ways would be used. After comparing the knee joint angle with interior and exterior movement of the knee in accordance with the joint dynamics of typical height, the walking pattern for walking up the stairs can be comprehended. It could be shown the variation of the center of rotation of knee joint. From this, the contact point which is pressed on the knee joints in accordance with each walking pattern could be derived. The numerical modeling could be made by quantifying the variety that is caused by the center of mass of knee bone. It would be expected to calculate the contact point on the knee joint through walking patterns. This numerical model is considered of the kinematics system in our knee

Nonflammable Lithium Metal Full Cells with Ultra-high Energy Density Based on Coordinated Carbonate Electrolytes

Coupling thin Li metal anodes with high-capacity/high-voltage cathodes such as LiNi0.8Co0.1Mn0.1O2 (NCM811) is a promising way to increase lithium battery energy density. Yet, the realization of high-performance full cells remains a formidable challenge. Here, we demonstrate a new class of highly coordinated, nonflammable carbonate electrolytes based on lithium bis(fluorosulfonyl)imide (UFSI) in propylene carbonate/fluoroethylene carbonate mixtures. Utilizing an optimal salt concentr ation (4 M LiFSI) of the electrolyte results in a unique coordination structure of Li+-FSI-solvent cluster, which is critical for enabling the formation of stable interfaces on both the thin Li metal anode and high-voltage NCM811 cathode. Under highly demanding cell configuration and operating conditions (Li metal anode = 35 mu m, areal capacity/charge voltage of NCM811 cathode = 4.8 mAh cm(-2)/4 .6 V, and anode excess capacity [relative to the cathode] = 0.83), the Li metal-based full cell provides exceptional electrochemical performance (energy densities = 679 Wh kg(cell)(-1)/1,024 Wh L-cell(-1)) coupled with nonflammability

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

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

Phosphorus in the Young Supernova Remnant Cassiopeia A

Phosphorus (^(31)P), which is essential for life, is thought to be synthesized in massive stars and dispersed into interstellar space when these stars explode as supernovae (SNe). Here, we report on near-infrared spectroscopic observations of the young SN remnant Cassiopeia A, which show that the abundance ratio of phosphorus to the major nucleosynthetic product iron (^(56)Fe) in SN material is up to 100 times the average ratio of the Milky Way, confirming that phosphorus is produced in SNe. The observed range is compatible with predictions from SN nucleosynthetic models but not with the scenario in which the chemical elements in the inner SN layers are completely mixed by hydrodynamic instabilities during the explosion

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

Determination of bit-rate and sensitivity limits of an optimized p-i-n/HBT OEIC receiver using SPICE simulations

The sensitivity of an OEIC receiver depends essentially on the physical sources of device and circuit noise referred to its input, provided that the inter-symbol interference (ISI) makes no significant contribution. For well designed receivers, the latter situation can be realized only at an optimum bandwidth (f3 dB-opt) for a given bit rate (B) or vice versa. In this paper, we have determined the relationship between the bit rate and the 3-dB bandwidth for negligible and pre-set levels of ISI for an optimized p-i-n/HBT transimpedance receiver with adjustable bandwidth.We have used the SPICE simulations in the frequency domain to determine the effect of device and circuit noise, and the SPICE transient analysis to determine the effect of ISI on the sensitivity. The ratio f3 dB-opt=B has been found to vary from 0.65 to 0.45 when B changes from 10 to 20 Gbps for the OEIC receiver used.This work was supported by the Korean Science and Engineering Foundation under Grant 94-X-0026, by the KAIST OptoElectronics Research Center (OERC), and also by the U.S. National Science Foundation under Grant ECS-9541739 (INT-9412658). The work of S. J. Kim was supported in part by the SeoAm Scholarship Foundation