Boston University

About: Boston University is a education organization based out in Boston, Massachusetts, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 48688 authors who have published 119622 publications receiving 6276020 citations. The organization is also known as: BU & Boston U.

Developmental Trauma Disorder: Toward a rational diagnosis for children with complex trauma histories.

Abstract: in helping to formulate the proposed diagnosis of Developmental Trauma Disorder.

Deep CORAL: Correlation Alignment for Deep Domain Adaptation

Abstract: Deep neural networks are able to learn powerful representations from large quantities of labeled input data, however they cannot always generalize well across changes in input distributions. Domain adaptation algorithms have been proposed to compensate for the degradation in performance due to domain shift. In this paper, we address the case when the target domain is unlabeled, requiring unsupervised adaptation. CORAL [18] is a simple unsupervised domain adaptation method that aligns the second-order statistics of the source and target distributions with a linear transformation. Here, we extend CORAL to learn a nonlinear transformation that aligns correlations of layer activations in deep neural networks (Deep CORAL). Experiments on standard benchmark datasets show state-of-the-art performance. Our code is available at: https://github.com/VisionLearningGroup/CORAL.

BRITE: an approach to universal topology generation

Abstract: Effective engineering of the Internet is predicated upon a detailed understanding of issues such as the large-scale structure of its underlying physical topology, the manner in which it evolves over time, and the way in which its constituent components contribute to its overall function. Unfortunately, developing a deep understanding of these issues has proven to be a challenging task, since it in turn involves solving difficult problems such as mapping the actual topology, characterizing it, and developing models that capture its emergent behavior. Consequently, even though there are a number of topology models, it is an open question as to how representative the generated topologies they generate are of the actual Internet. Our goal is to produce a topology generation framework which improves the state of the art and is based on the design principles of representativeness, inclusiveness, and interoperability. Representativeness leads to synthetic topologies that accurately reflect many aspects of the actual Internet topology (e.g. hierarchical structure, node degree distribution, etc.). Inclusiveness combines the strengths of as many generation models as possible in a single generation tool. Interoperability provides interfaces to widely-used simulation applications such as ns and SSF and visualization tools like otter. We call such a tool a universal topology generator.

Cutting edge: recognition of Gram-positive bacterial cell wall components by the innate immune system occurs via Toll-like receptor 2

Abstract: Invasive infection with Gram-positive and Gram-negative bacteria often results in septic shock and death. The basis for the earliest steps in innate immune response to Gram-positive bacterial infection is poorly understood. The LPS component of the Gram-negative bacterial cell wall appears to activate cells via CD14 and Toll-like receptor (TLR) 2 and TLR4. We hypothesized that Gram-positive bacteria might also be recognized by TLRs. Heterologous expression of human TLR2, but not TLR4, in fibroblasts conferred responsiveness to Staphylococcus aureus and Streptococcus pneumoniae as evidenced by inducible translocation of NF-kappaB. CD14 coexpression synergistically enhanced TLR2-mediated activation. To determine which components of Gram-positive cell walls activate Toll proteins, we tested a soluble preparation of peptidoglycan prepared from S. aureus. Soluble peptidoglycan substituted for whole organisms. These data suggest that the similarity of clinical response to invasive infection by Gram-positive and Gram-negative bacteria is due to bacterial recognition via similar TLRs.