University of California, Irvine

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.

Mild cognitive impairment can be distinguished from Alzheimer disease and normal aging for clinical trials.

Abstract: Background Mild cognitive impairment (MCI) represents a transitional state between the cognitive changes of normal aging and very early dementia and is becoming increasingly recognized as a risk factor for Alzheimer disease (AD). The Memory Impairment Study (MIS) is a multicenter clinical trial in patients with MCI designed to evaluate whether vitamin E or donepezil is effective at delaying the time to a clinical diagnosis of AD. Objective To describe the baseline characteristics of patients with MCI recruited for the MIS and compare them with those of elderly controls and patients with AD in another clinical trial. Design Descriptive and comparative study of patients with MCI participating in a multicenter clinical trial. Setting Memory disorder centers in the United States and Canada. Patients A total of 769 patients with MCI, 107 cognitively normal elderly controls, 122 patients with very mild AD (Clinical Dementia Rating [CDR] 0.5), and 183 patients with mild AD (CDR 1.0) were evaluated. Patients in the MIS met operational criteria for amnestic MCI. Controls were recruited in parallel with the MCI group, underwent the same assessments, and had a CDR of 0. Main Outcome Measures Clinical, neuropsychologic, functional, neuroimaging, and genetic measures. Results Mean ± SD Alzheimer's Disease Assessment Scale–Cognitive Subscale scores were 5.6 ± 3.3 for controls, 11.3 ± 4.4 for patients with MCI, 18.0 ± 6.2 for the AD CDR 0.5 group, and 25.2 ± 8.8 for the AD CDR 1.0 group. Compared with controls, patients with MCI were most impaired on memory tasks, with less severe impairments in other cognitive domains. Patients with MCI were more likely than controls but less likely than patients with AD to carry the apolipoprotein E ϵ4 allele. Patients with MCI had hippocampal volumes that were intermediate between those of controls and patients with AD. Conclusions Patients with MCI had a predominant memory impairment with relative sparing of other cognitive domains and were intermediate between clinically normal individuals and patients with AD on cognitive and functional ratings. These results demonstrate the successful implementation of operational criteria for this unique group of at-risk patients in a multicenter clinical trial.

Articulated Human Detection with Flexible Mixtures of Parts

Abstract: We describe a method for articulated human detection and human pose estimation in static images based on a new representation of deformable part models. Rather than modeling articulation using a family of warped (rotated and foreshortened) templates, we use a mixture of small, nonoriented parts. We describe a general, flexible mixture model that jointly captures spatial relations between part locations and co-occurrence relations between part mixtures, augmenting standard pictorial structure models that encode just spatial relations. Our models have several notable properties: 1) They efficiently model articulation by sharing computation across similar warps, 2) they efficiently model an exponentially large set of global mixtures through composition of local mixtures, and 3) they capture the dependency of global geometry on local appearance (parts look different at different locations). When relations are tree structured, our models can be efficiently optimized with dynamic programming. We learn all parameters, including local appearances, spatial relations, and co-occurrence relations (which encode local rigidity) with a structured SVM solver. Because our model is efficient enough to be used as a detector that searches over scales and image locations, we introduce novel criteria for evaluating pose estimation and human detection, both separately and jointly. We show that currently used evaluation criteria may conflate these two issues. Most previous approaches model limbs with rigid and articulated templates that are trained independently of each other, while we present an extensive diagnostic evaluation that suggests that flexible structure and joint training are crucial for strong performance. We present experimental results on standard benchmarks that suggest our approach is the state-of-the-art system for pose estimation, improving past work on the challenging Parse and Buffy datasets while being orders of magnitude faster.

The economics of urban transportation

Abstract: 1 Introduction 2 Travel Demand 3 Costs 4 Pricing 5 Investment 6 Industrial Organization of Transportation Providers 7 Conclusion

Bundling Information Goods: Pricing, Profits, and Efficiency

Abstract: We study the strategy of bundling a large number of information goods, such as those increasingly available on the Internet, and selling them for a fixed price. We analyze the optimal bundling strategies for a multiproduct monopolist, and we find that bundling very large numbers of unrelated information goods can be surprisingly profitable. The reason is that the law of large numbers makes it much easier to predict consumers' valuations for a bundle of goods than their valuations for the individual goods when sold separately. As a result, this "predictive value of bundling" makes it possible to achieve greater sales, greater economic efficiency, and greater profits per good from a bundle of information goods than can be attained when the same goods are sold separately. Our main results do not extend to most physical goods, as the marginal costs of production for goods not used by the buyer typically negate any benefits from the predictive value of large-scale bundling. While determining optimal bundling strategies for more than two goods is a notoriously difficult problem, we use statistical techniques to provide strong asymptotic results and bounds on profits for bundles of any arbitrary size. We show how our model can be used to analyze the bundling of complements and substitutes, bundling in the presence of budget constraints, and bundling of goods with various types of correlations and how each of these conditions can lead to limits on optimal bundle size. In particular we find that when different market segments of consumers differ systematically in their valuations for goods, simple bundling will no longer be optimal. However, by offering a menu of different bundles aimed at each market segment, bundling makes traditional price discrimination strategies more powerful by reducing the role of unpredictable idiosyncratic components of valuations. The predictions of our analysis appear to be consistent with empirical observations of the markets for Internet and online content, cable television programming, and copyrighted music.