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Institution

University of Texas at Dallas

EducationRichardson, Texas, United States
About: University of Texas at Dallas is a education organization based out in Richardson, Texas, United States. It is known for research contribution in the topics: Population & Computer science. The organization has 14986 authors who have published 35589 publications receiving 1293714 citations. The organization is also known as: UT-Dallas & UT Dallas.


Papers
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Journal ArticleDOI
01 Oct 2010-ACS Nano
TL;DR: IR spectroscopy, XPS analysis, and DFT calculations all confirm that the water molecules play a significant role interacting with basal plane etch holes through passivation, via evolution of CO(2) leading to the formation of ketone and ester carbonyl groups.
Abstract: A detailed in situ infrared spectroscopy analysis of single layer and multilayered graphene oxide (GO) thin films reveals that the normalized infrared absorption in the carbonyl region is substantially higher in multilayered GO upon mild annealing. These results highlight the fact that the reduction chemistry of multilayered GO is dramatically different from the single layer GO due to the presence of water molecules confined in the ∼1 nm spacing between sheets. IR spectroscopy, XPS analysis, and DFT calculations all confirm that the water molecules play a significant role interacting with basal plane etch holes through passivation, via evolution of CO2 leading to the formation of ketone and ester carbonyl groups. Displacement of water from intersheet spacing with alcohol significantly changes the chemistry of carbonyl formation with temperature.

356 citations

Proceedings ArticleDOI
15 Oct 2018
TL;DR: This paper develops techniques that reduce the complexity of the inference of global properties of the training data, such as the environment in which the data was produced, or the fraction of the data that comes from a certain class, as applied to white-box Fully Connected Neural Networks (FCNNs).
Abstract: With the growing adoption of machine learning, sharing of learned models is becoming popular. However, in addition to the prediction properties the model producer aims to share, there is also a risk that the model consumer can infer other properties of the training data the model producer did not intend to share. In this paper, we focus on the inference of global properties of the training data, such as the environment in which the data was produced, or the fraction of the data that comes from a certain class, as applied to white-box Fully Connected Neural Networks (FCNNs). Because of their complexity and inscrutability, FCNNs have a particularly high risk of leaking unexpected information about their training sets; at the same time, this complexity makes extracting this information challenging. We develop techniques that reduce this complexity by noting that FCNNs are invariant under permutation of nodes in each layer. We develop our techniques using representations that capture this invariance and simplify the information extraction task. We evaluate our techniques on several synthetic and standard benchmark datasets and show that they are very effective at inferring various data properties. We also perform two case studies to demonstrate the impact of our attack. In the first case study we show that a classifier that recognizes smiling faces also leaks information about the relative attractiveness of the individuals in its training set. In the second case study we show that a classifier that recognizes Bitcoin mining from performance counters also leaks information about whether the classifier was trained on logs from machines that were patched for the Meltdown and Spectre attacks.

356 citations

Journal ArticleDOI
TL;DR: The effects of ASOC on the superconducting properties and the extent to which there is evidence for singlet-triplet mixing are evaluated and a conceptual overview of the key theoretical results are given.
Abstract: In non-centrosymmetric superconductors, where the crystal structure lacks a centre of inversion, parity is no longer a good quantum number and an electronic antisymmetric spin-orbit coupling (ASOC) is allowed to exist by symmetry. If this ASOC is sufficiently large, it has profound consequences on the superconducting state. For example, it generally leads to a superconducting pairing state which is a mixture of spin-singlet and spin-triplet components. The possibility of such novel pairing states, as well as the potential for observing a variety of unusual behaviors, led to intensive theoretical and experimental investigations. Here we review the experimental and theoretical results for superconducting systems lacking inversion symmetry. Firstly we give a conceptual overview of the key theoretical results. We then review the experimental properties of both strongly and weakly correlated bulk materials, as well as two dimensional systems. Here the focus is on evaluating the effects of ASOC on the superconducting properties and the extent to which there is evidence for singlet-triplet mixing. This is followed by a more detailed overview of theoretical aspects of non-centrosymmetric superconductivity. This includes the effects of the ASOC on the pairing symmetry and the superconducting magnetic response, magneto-electric effects, superconducting finite momentum pairing states, and the potential for non-centrosymmetric superconductors to display topological superconductivity.

355 citations

Journal ArticleDOI
TL;DR: This review is a condensed and updated summary of practice guidelines for optimizing bone health in patients with CF, a statement that evolved from a meeting convened by the Cystic Fibrosis Foundation in May 2002 to address the pathogenesis, diagnosis, and treatment of bone disease in CF.
Abstract: Cystic fibrosis (CF) is the most common genetic disease within the Caucasian population and leads to premature respiratory failure. Approximately 60,000 individuals are currently living with CF in North America and Europe, 40% of whom are adults. Thelifespanofthesepatientshasincreasedfromapproximately 2 to 32 yr of age over the last three decades. Bone disease has emerged as a common complication in long-term survivors of CF. Some studies have observed that 50–75% of adults have low bone density and increased rates of fractures. Prevention and treatment of CF-related bone disease must address the myriad risk factors (decreased absorption of fat-soluble vitamins due to pancreatic insufficiency, altered sex hormone production, chronic lung infection with increased levels of bone-active cytokines, physical inactivity, and glucocorticoid therapy) for poor bone health. This review is a condensed and updated summaryoftheGuidetoBoneHealthandDiseaseinCysticFibrosis: A Consensus Conference, a statement that evolved from a meeting convened by the Cystic Fibrosis Foundation in May 2002 to address the pathogenesis, diagnosis, and treatment of bone disease in CF. The goal of this conference was to develop practice guidelines for optimizing bone health in patients with CF. (J Clin Endocrinol Metab 90: 1888–1896, 2005)

355 citations

Journal ArticleDOI
TL;DR: The authors disentangles the disruption effects of moves from changes in SQ and identifies the negative externality movers impose on other students, and shows that student turnover is associated with a substantial cost for movers and non-movers alike.

355 citations


Authors

Showing all 15148 results

NameH-indexPapersCitations
Eugene Braunwald2301711264576
Younan Xia216943175757
Eric N. Olson206814144586
Thomas C. Südhof191653118007
Scott M. Grundy187841231821
Jing Wang1844046202769
Eric Boerwinkle1831321170971
Eric J. Nestler178748116947
John D. Minna169951106363
Elliott M. Antman161716179462
Adi F. Gazdar157776104116
Bruce D. Walker15577986020
R. Kowalewski1431815135517
Joseph Izen137143398900
James A. Richardson13636375778
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
202371
2022217
20212,152
20202,227
20192,192