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Institution

University of California, Irvine

EducationIrvine, California, United States
About: University of California, Irvine is a education organization based out in Irvine, California, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 47031 authors who have published 113602 publications receiving 5521832 citations. The organization is also known as: UC Irvine & UCI.


Papers
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Journal ArticleDOI
TL;DR: A range of remarkable characteristics of ZnO nanostructures are presented, organized into sections describing the mechanical, electrical, optical, magnetic, and chemical sensing properties.
Abstract: This article provides a comprehensive review of the current research activities that focus on the ZnO nanostructure materials and their physical property characterizations. It begins with the synthetic methods that have been exploited to grow ZnO nanostructures. A range of remarkable characteristics are then presented, organized into sections describing the mechanical, electrical, optical, magnetic, and chemical sensing properties. These studies constitute the basis for developing versatile applications of ZnO nanostructures.

758 citations

Proceedings ArticleDOI
16 Jun 2012
TL;DR: This work presents a novel dataset and novel algorithms for the problem of detecting activities of daily living in firstperson camera views, and develops novel representations including temporal pyramids and composite object models that exploit the fact that objects look different when being interacted with.
Abstract: We present a novel dataset and novel algorithms for the problem of detecting activities of daily living (ADL) in firstperson camera views. We have collected a dataset of 1 million frames of dozens of people performing unscripted, everyday activities. The dataset is annotated with activities, object tracks, hand positions, and interaction events. ADLs differ from typical actions in that they can involve long-scale temporal structure (making tea can take a few minutes) and complex object interactions (a fridge looks different when its door is open). We develop novel representations including (1) temporal pyramids, which generalize the well-known spatial pyramid to approximate temporal correspondence when scoring a model and (2) composite object models that exploit the fact that objects look different when being interacted with. We perform an extensive empirical evaluation and demonstrate that our novel representations produce a two-fold improvement over traditional approaches. Our analysis suggests that real-world ADL recognition is “all about the objects,” and in particular, “all about the objects being interacted with.”

757 citations

Journal ArticleDOI
09 Aug 1991-Cell
TL;DR: Small (100-260 kb), nested deletions were characterized in DNA from two unrelated patients with familial adenomatous polyposis coli (APC) and two new genes contained sequence identical to SRP19, the gene coding for the 19 kd component of the ribosomal signal recognition particle.

756 citations

Proceedings Article
04 Aug 1996
TL;DR: The naive Bayesian classifier offers several advantages over other learning algorithms on this task and an initial portion of a web page is sufficient for making predictions on its interestingness substantially reducing the amount of network transmission required to make predictions.
Abstract: We describe Syskill & Webert, a software agent that learns to rate pages on the World Wide Web (WWW), deciding what pages might interest a user. The user rates explored pages on a three point scale, and Syskill & Webert learns a user profile by analyzing the information on each page. The user profile can be used in two ways. First, it can be used to suggest which links a user would be interested in exploring. Second, it can be used to construct a LYCOS query to find pages that would interest a user. We compare six different algorithms from machine learning and information retrieval on this task. We find that the naive Bayesian classifier offers several advantages over other learning algorithms on this task. Furthermore, we find that an initial portion of a web page is sufficient for making predictions on its interestingness substantially reducing the amount of network transmission required to make predictions.

756 citations

Journal ArticleDOI
01 Jun 2010-Headache
TL;DR: OnabotulinumtoxinA (BOTOX®) as discussed by the authors is an effective prophylactic treatment for chronic migraine in adults with chronic migraines and showed significant improvements compared with placebo in multiple headache symptom measures and significantly reduced headache-related disability and improved functioning, vitality, and overall health-related quality of life.
Abstract: (Headache 2010;50:921-936) Objective.— To assess the efficacy, safety, and tolerability of onabotulinumtoxinA (BOTOX®) as headache prophylaxis in adults with chronic migraine. Background.— Chronic migraine is a prevalent, disabling, and undertreated neurological disorder. Few preventive treatments have been investigated and none is specifically indicated for chronic migraine. Methods.— The 2 multicenter, pivotal trials in the PREEMPT: Phase 3 REsearch Evaluating Migraine Prophylaxis Therapy clinical program each included a 24-week randomized, double-blind phase followed by a 32-week open-label phase (ClinicalTrials.gov identifiers NCT00156910, NCT00168428). Qualified patients were randomized (1:1) to onabotulinumtoxinA (155-195 U) or placebo injections every 12 weeks. Study visits occurred every 4 weeks. These studies were identical in design (eg, inclusion/exclusion criteria, randomization, visits, double-blind phase, open-label phase, safety assessments, treatment), with the only exception being the designation of the primary and secondary endpoints. Therefore, the predefined pooling of the results was justified and performed to provide a complete overview of between-group differences in efficacy, safety, and tolerability that may not have been evident in individual studies. The primary endpoint for the pooled analysis was mean change from baseline in frequency of headache days at 24 weeks. Secondary endpoints were mean change from baseline to week 24 in frequency of migraine/probable migraine days, frequency of moderate/severe headache days, total cumulative hours of headache on headache days, frequency of headache episodes, frequency of migraine/probable migraine episodes, frequency of acute headache pain medication intakes, and the proportion of patients with severe (≥60) Headache Impact Test-6 score at week 24. Results of the pooled analyses of the 2 PREEMPT double-blind phases are presented. Results.— A total of 1384 adults were randomized to onabotulinumtoxinA (n = 688) or placebo (n = 696). Pooled analyses demonstrated a large mean decrease from baseline in frequency of headache days, with statistically significant between-group differences favoring onabotulinumtoxinA over placebo at week 24 (−8.4 vs −6.6; P < .001) and at all other time points. Significant differences favoring onabotulinumtoxinA were also observed for all secondary efficacy variables at all time points, with the exception of frequency of acute headache pain medication intakes. Adverse events occurred in 62.4% of onabotulinumtoxinA patients and 51.7% of placebo patients. Most patients reported adverse events that were mild to moderate in severity and few discontinued (onabotulinumtoxinA, 3.8%; placebo, 1.2%) due to adverse events. No unexpected treatment-related adverse events were identified. Conclusions.— The pooled PREEMPT results demonstrate that onabotulinumtoxinA is an effective prophylactic treatment for chronic migraine. OnabotulinumtoxinA resulted in significant improvements compared with placebo in multiple headache symptom measures, and significantly reduced headache-related disability and improved functioning, vitality, and overall health-related quality of life. Repeat treatments with onabotulinumtoxinA were safe and well tolerated.

755 citations


Authors

Showing all 47751 results

NameH-indexPapersCitations
Daniel Levy212933194778
Rob Knight2011061253207
Lewis C. Cantley196748169037
Dennis W. Dickson1911243148488
Terrie E. Moffitt182594150609
Joseph Biederman1791012117440
John R. Yates1771036129029
John A. Rogers1771341127390
Avshalom Caspi170524113583
Yang Gao1682047146301
Carl W. Cotman165809105323
John H. Seinfeld165921114911
Gregg C. Fonarow1611676126516
Jerome I. Rotter1561071116296
David Cella1561258106402
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20242
2023252
20221,224
20216,519
20206,348
20195,610