Prevention of Fungal Growth on Rubber Earpads of Telecommunication Equipments

This paper recommends an addition of 100% zinc oxide to the rubber composition during its manufacture to effectively prevent fungal growth on the earpads without producing any adverse on its materials/performance or the user

Properties of radioactive wastes and waste containers

This program is sponsored by the Nuclear Regulatory Commission to address basic concerns in assessing the performance of solidified radwaste. Experiments were initiated to address these concerns. In particular, leachability of solidified radwastes and the physical stability of the ensuing waste forms were evaluated. In addition, leaching experiments designed to address the effects of alternating wet/dry cycles and of varying the length of these cycles on the leach behavior of waste forms were initiated

Mid-infrared imaging of the massive young star AFGL 2591: Probing the circumstellar environment of an outflow source

Most, if not all, stars are now believed to produce energetic outflows during their formation. Yet, almost 20 years after the discovery of bipolar outflows from young stars, the origins of this violent phenomenon are not well understood. One of the difficulties of probing the outflow process, particularly in the case of massive embedded stars, is a deficit of high spatial resolution observations. Here, we present sub-arcsecond-resolution mid-infrared images of one massive young stellar object, AFGL 2591, and its immediate surroundings. Our images, at 11.7, 12.5 and 18.0 microns, reveal a knot of emission ~6'' SW of the star, which may be evidence for a recent ejection event or an embedded companion star. This knot is roughly coincident with a previously seen near-infrared reflection nebula and a radio source, and lies within the known large-scale CO outflow. We also find a new faint NW source which may be another embedded lower-luminosity star. The IRAS mid-infrared spectrum of AFGL 2591 shows a large silicate absorption feature at 10 microns, implying that the primary source is surrounded by an optically thick dusty envelope. We discuss the interrelationship of these phenomena and suggest that mid-infrared imaging and spectroscopy provide powerful tools for probing massive star birth.Comment: 14 pages, 3 PostScript figures, accepted for publication in The Astrophysical Journal Letter

Performance Limitations of Flat Histogram Methods and Optimality of Wang-Landau Sampling

We determine the optimal scaling of local-update flat-histogram methods with system size by using a perfect flat-histogram scheme based on the exact density of states of 2D Ising models.The typical tunneling time needed to sample the entire bandwidth does not scale with the number of spins N as the minimal N^2 of an unbiased random walk in energy space. While the scaling is power law for the ferromagnetic and fully frustrated Ising model, for the +/- J nearest-neighbor spin glass the distribution of tunneling times is governed by a fat-tailed Frechet extremal value distribution that obeys exponential scaling. We find that the Wang-Landau algorithm shows the same scaling as the perfect scheme and is thus optimal.Comment: 5 pages, 6 figure

MADG: Margin-based Adversarial Learning for Domain Generalization

Domain Generalization (DG) techniques have emerged as a popular approach to address the challenges of domain shift in Deep Learning (DL), with the goal of generalizing well to the target domain unseen during the training. In recent years, numerous methods have been proposed to address the DG setting, among which one popular approach is the adversarial learning-based methodology. The main idea behind adversarial DG methods is to learn domain-invariant features by minimizing a discrepancy metric. However, most adversarial DG methods use 0-1 loss based $\mathcal{H}\Delta\mathcal{H}$ divergence metric. In contrast, the margin loss-based discrepancy metric has the following advantages: more informative, tighter, practical, and efficiently optimizable. To mitigate this gap, this work proposes a novel adversarial learning DG algorithm, MADG, motivated by a margin loss-based discrepancy metric. The proposed MADG model learns domain-invariant features across all source domains and uses adversarial training to generalize well to the unseen target domain. We also provide a theoretical analysis of the proposed MADG model based on the unseen target error bound. Specifically, we construct the link between the source and unseen domains in the real-valued hypothesis space and derive the generalization bound using margin loss and Rademacher complexity. We extensively experiment with the MADG model on popular real-world DG datasets, VLCS, PACS, OfficeHome, DomainNet, and TerraIncognita. We evaluate the proposed algorithm on DomainBed's benchmark and observe consistent performance across all the datasets

Reionization with galaxies and active galactic nuclei

In this work we investigate the properties of the sources that reionized the intergalactic medium (IGM) in the high-redshift Universe. Using a semi-Analytical model aimed at reproducing galaxies and black holes in the first ∼1.5 Gyr of the Universe, we revisit the relative role of star formation and black hole accretion in producing ionizing photons that can escape into the IGM. Both star formation and black hole accretion are regulated by supernova feedback, resulting in black hole accretion being stunted in low-mass haloes. We explore a wide range of combinations for the escape fraction of ionizing photons (redshift-dependent, constant, and scaling with stellar mass) from both star formation ($langle f_{ m esc}^{ m sf} angle$) and AGN ($f_{ m esc}^{ m bh}$) to find: (i) the ionizing budget is dominated by stellar radiation from low stellar mass ($M_∗lt 10^9 , { m m M_odot }$) galaxies at z > 6 with the AGN contribution (driven by $M_{bh}gt 10^6 , { m m M_odot }$ black holes in $M_∗ gtrsim 10^9, { m m M_odot }$ galaxies) dominating at lower redshifts; (ii) AGN only contribute $10-25{{ m per cent}}$ to the cumulative ionizing emissivity by z = 4 for the models that match the observed reionization constraints; (iii) if the stellar mass dependence of $langle f_{ m esc}^{ m sf} angle$ is shallower than $f_{ m esc}^{ m bh}$, at z < 7 a transition stellar mass exists above which AGN dominate the escaping ionizing photon production rate; (iv) the transition stellar mass decreases with decreasing redshift. While AGN dominate the escaping emissivity above the knee of the stellar mass function at z ∼6.8, they take-over at stellar masses that are a tenth of the knee mass by z = 4

Genetic divergence study in greengram [Vigna radiata (L.) Wilczek]

The present investigation was undertaken to obtain information on the nature and extent of genetic diversity among 60 greengram genotypes for yield related traits and quality traits by using Mahalanobis’s D2 statistics. The genotypes were grouped into eleven clusters. Cluster I was found to be the largest with 38 genotypes followed by cluster V with 13 genotypes and all the other clusters were found to be solitary, each containing a single genotype. Clusters VIII and XI had the maximum inter-cluster distance, followed by clusters IV and XI. Cluster XI had the highest mean values for yield and other yield attributing traits. Iron content contributed high towards total genetic diversity followed by protein content and test weight. Based on the mean performance and diversity studies, the genotypes COGG 18-17, LGG 460, Daftri vikas and IPM 1603-3 were found to be the best for further yield improvement in greengram. Utilizing the genotypes from the more divergent clusters as parents in breeding programmes will yield relatively good amount of heterosis in F1 and high frequency of transgressive segregants and genetic variability in subsequent generations can be acquired