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Providence, RI, United States

Brown University is a private Ivy League research university in Providence, Rhode Island.Founded in 1764 as "The College in the English Colony of Rhode Island and Providence Plantations," Brown is the seventh-oldest institution of higher education in the United States and one of the nine Colonial Colleges established before the American Revolution. At its foundation, Brown was the first college in the United States to accept students regardless of their religious affiliation. Its engineering program, established in 1847, was the first in what is now known as the Ivy League. Brown's New Curriculum—sometimes referred to in education theory as the Brown Curriculum—was adopted by faculty vote in 1969 after a period of student lobbying; the New Curriculum eliminated mandatory "general education" distribution requirements, made students "the architects of their own syllabus," and allowed them to take any course for a grade of satisfactory or unrecorded no-credit. In 1971, Brown's coordinate women's institution, Pembroke College was fully merged into the university.The undergraduate acceptance rate is among the country's most selective with an acceptance rate of 8.6% for the class of 2018. The University comprises The College, the Graduate School, Alpert Medical School, the School of Engineering, the School of Public Health, and the School of Professional Studies . Brown's international programs are organized through the Watson Institute for International Studies. The Brown/RISD Dual Degree Program, offered in conjunction with the Rhode Island School of Design, is a five-year course that awards degrees from both institutions.Brown's main campus is located in the College Hill Historic District in the city of Providence, the second largest city in New England. The University's neighborhood is a federally listed architectural district with a dense concentration of ancient buildings. On the western edge of the campus, Benefit Street contains "one of the finest cohesive collections of restored seventeenth- and eighteenth-century architecture in the United States".Brown University is home to many prominent alumni, known as Brunonians, including current president of the World Bank Jim Yong Kim and Chair of the Federal Reserve Janet Yellen. While considered a small research university, Brown has been affiliated with 7 Nobel laureates as students, faculty, or staff. It has been associated with 54 Rhodes Scholars, 5 National Humanities Medalists, 10 National Medal of Science laureates, and is a leading producer of Fulbright Scholars. Wikipedia.


Gao H.,Brown University
Journal of the Mechanics and Physics of Solids | Year: 2014

With the rapid development of nanotechnology, various types of nanoparticles, nanowires, nanofibers, nanotubes, and atomically thin plates and sheets have emerged as candidates for an ever increasing list of potential applications for next generation electronics, microchips, composites, barrier coatings, biosensors, drug delivery, and energy harvesting and conversion systems. There is now an urgent societal need to understand both beneficial and hazardous effects of nanotechnology which is projected to produce and release thousands of tons of nanomaterials into the environment in the coming decades. This paper aims to present an overview of some recent studies conducted at Brown University on the mechanics of cell-nanomaterial interactions, including the modeling of nanoparticles entering cells by receptor-mediated endocytosis and coarse-grained molecular dynamics simulations of nanoparticles interacting with cell membranes. The discussions will be organized around the following questions: Why and how does cellular uptake of nanoparticles depend on particle size, shape, elasticity and surface structure? In particular, we will discuss the effect of nanoparticle size on receptor-mediated endocytosis, the effect of elastic stiffness on cell-particle interactions, how high aspect ratio nanomaterials such as carbon nanotubes and graphenes enter cells and how different geometrical patterns of ligands on a nanoparticle can be designed to control the rate of particle uptake. © 2013 Elsevier Ltd. All rights reserved.


Littman M.L.,Brown University
Nature | Year: 2015

Reinforcement learning is a branch of machine learning concerned with using experience gained through interacting with the world and evaluative feedback to improve a system's ability to make behavioural decisions. It has been called the artificial intelligence problem in a microcosm because learning algorithms must act autonomously to perform well and achieve their goals. Partly driven by the increasing availability of rich data, recent years have seen exciting advances in the theory and practice of reinforcement learning, including developments in fundamental technical areas such as generalization, planning, exploration and empirical methodology, leading to increasing applicability to real-life problems. © 2015 Macmillan Publishers Limited. All rights reserved.


Cavanagh J.F.,University of New Mexico | Frank M.J.,Brown University
Trends in Cognitive Sciences | Year: 2014

Recent advancements in cognitive neuroscience have afforded a description of neural responses in terms of latent algorithmic operations. However, the adoption of this approach to human scalp electroencephalography (EEG) has been more limited, despite the ability of this methodology to quantify canonical neuronal processes. Here, we provide evidence that theta band activities over the midfrontal cortex appear to reflect a common computation used for realizing the need for cognitive control. Moreover, by virtue of inherent properties of field oscillations, these theta band processes may be used to communicate this need and subsequently implement such control across disparate brain regions. Thus, frontal theta is a compelling candidate mechanism by which emergent processes, such as 'cognitive control', may be biophysically realized. © 2014 Elsevier Ltd.


Although tumor size and lymph node involvement are the current cornerstones of breast cancer prognosis, they have not been extensively explored in relation to tumor methylation attributes in conjunction with other tumor and patient dietary and hormonal characteristics. Using primary breast tumors from 162 (AJCC stage I-IV) women from the Kaiser Division of Research Pathways Study and the Illumina GoldenGate methylation bead-array platform, we measured 1,413 autosomal CpG loci associated with 773 cancer-related genes and validated select CpG loci with Sequenom EpiTYPER. Tumor grade, size, estrogen and progesterone receptor status, and triple negative status were significantly (Q-values <0.05) associated with altered methylation of 209, 74, 183, 69, and 130 loci, respectively. Unsupervised clustering, using a recursively partitioned mixture model (RPMM), of all autosomal CpG loci revealed eight distinct methylation classes. Methylation class membership was significantly associated with patient race (P<0.02) and tumor size (P<0.001) in univariate tests. Using multinomial logistic regression to adjust for potential confounders, patient age and tumor size, as well as known disease risk factors of alcohol intake and total dietary folate, were all significantly (P<0.0001) associated with methylation class membership. Breast cancer prognostic characteristics and risk-related exposures appear to be associated with gene-specific tumor methylation, as well as overall methylation patterns.


De la Monte S.M.,Brown University
European Neuropsychopharmacology | Year: 2014

Alzheimer-s disease (AD) is the most common cause of dementia in North America. Growing evidence supports the concept that AD is a metabolic disease mediated by impairments in brain insulin responsiveness, glucose utilization, and energy metabolism, which lead to increased oxidative stress, inflammation, and worsening of insulin resistance. In addition, metabolic derangements directly contribute to the structural, functional, molecular, and biochemical abnormalities that characterize AD, including neuronal loss, synaptic disconnection, tau hyperphosphorylation, and amyloid-beta accumulation. Because the fundamental abnormalities in AD represent effects of brain insulin resistance and deficiency, and the molecular and biochemical consequences overlap with Type 1 and Type 2 diabetes, we suggest the term "Type 3 diabetes" to account for the underlying abnormalities associated with AD-type neurodegeneration. In light of the rapid increases in sporadic AD prevalence rates and vastly expanded use of nitrites and nitrates in foods and agricultural products over the past 30-40 years, the potential role of nitrosamine exposures as mediators of Type 3 diabetes is discussed. © 2014 Elsevier B.V. and ECNP.

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