Brown University

About: Brown University is a education organization based out in Providence, Rhode Island, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 35778 authors who have published 90896 publications receiving 4471489 citations. The organization is also known as: brown.edu & Brown.

Mortality, CD4 Cell Count Decline, and Depressive Symptoms Among HIV-Seropositive Women: Longitudinal Analysis From the HIV Epidemiology Research Study

Abstract: ContextThe impact of depression on morbidity and mortality among women with human immunodeficiency virus (HIV) has not been examined despite the fact that women with HIV have substantially higher rates of depression than their male counterparts.ObjectiveTo determine the association of depressive symptoms with HIV-related mortality and decline in CD4 lymphocyte counts among women with HIV.DesignThe HIV Epidemiologic Research Study, a prospective, longitudinal cohort study conducted from April 1993 through January 1995, with follow-up through March 2000.SettingFour academic medical centers in Baltimore, Md; Bronx, NY; Providence, RI; and Detroit, Mich.ParticipantsA total of 765 HIV-seropositive women aged 16 to 55 years.Main Outcome MeasuresHIV-related mortality and CD4 cell count slope decline over a maximum of 7 years, compared among women with limited or no depressive symptoms, intermittent depressive symptoms, or chronic depressive symptoms, as measured using the self-report Center for Epidemiologic Studies Depression Scale.ResultsIn multivariate analyses controlling for clinical, treatment, and other factors, women with chronic depressive symptoms were 2 times more likely to die than women with limited or no depressive symptoms (relative risk [RR], 2.0; 95% confidence interval [CI], 1.0-3.8). Among women with CD4 cell counts of less than 200 × 106/L, HIV-related mortality rates were 54% for those with chronic depressive symptoms (RR, 4.3; 95% CI, 1.6-11.6) and 48% for those with intermittent depressive symptoms (RR, 3.5; 95% CI, 1.1-10.5) compared with 21% for those with limited or no depressive symptoms. Chronic depressive symptoms were also associated with significantly greater decline in CD4 cell counts after controlling for other variables in the model, especially among women with baseline CD4 cell counts of less than 500 × 106/L and baseline viral load greater than 10 000 copies/µL.ConclusionsOur results indicate that depressive symptoms among women with HIV are associated with HIV disease progression, controlling for clinical, substance use, and sociodemographic characteristics. These results highlight the importance of adequate diagnosis and treatment of depression among women with HIV. Further research is needed to determine if treatment of depression can not only enhance the mental health of women with HIV but also impede disease progression and mortality.

Towards Understanding Action Recognition

Abstract: Although action recognition in videos is widely studied, current methods often fail on real-world datasets. Many recent approaches improve accuracy and robustness to cope with challenging video sequences, but it is often unclear what affects the results most. This paper attempts to provide insights based on a systematic performance evaluation using thoroughly-annotated data of human actions. We annotate human Joints for the HMDB dataset (J-HMDB). This annotation can be used to derive ground truth optical flow and segmentation. We evaluate current methods using this dataset and systematically replace the output of various algorithms with ground truth. This enables us to discover what is important - for example, should we work on improving flow algorithms, estimating human bounding boxes, or enabling pose estimation? In summary, we find that high-level pose features greatly outperform low/mid level features, in particular, pose over time is critical, but current pose estimation algorithms are not yet reliable enough to provide this information. We also find that the accuracy of a top-performing action recognition framework can be greatly increased by refining the underlying low/mid level features, this suggests it is important to improve optical flow and human detection algorithms. Our analysis and J-HMDB dataset should facilitate a deeper understanding of action recognition algorithms.

The Global Topography of Mars and Implications for Surface Evolution

Abstract: Elevations measured by the Mars Orbiter Laser Altimeter have yielded a high-accuracy global map of the topography of Mars. Dominant features include the low northern hemisphere, the Tharsis province, and the Hellas impact basin. The northern hemisphere depression is primarily a long-wavelength effect that has been shaped by an internal mechanism. The topography of Tharsis consists of two broad rises. Material excavated from Hellas contributes to the high elevation of the southern hemisphere and to the scarp along the hemispheric boundary. The present topography has three major drainage centers, with the northern lowlands being the largest. The two polar cap volumes yield an upper limit of the present surface water inventory of 3.2 to 4.7 million cubic kilometers.

Efficient stochastic generation of special quasirandom structures

Abstract: We present a new algorithm to generate Special Quasirandom Structures (SQS), i.e., best periodic supercell approximations to the true disordered state for a given number of atoms per supercell. The method is based on a Monte Carlo simulated annealing loop with an objective function that seeks to perfectly match the maximum number of correlation functions (as opposed to merely minimizing the distance between the SQS correlation and the disordered state correlations for a pre-specified set of correlations). The proposed method optimizes the shape of the supercell jointly with the occupation of the atomic sites, thus ensuring that the configurational space searched is exhaustive and not biased by a pre-specified supercell shape. The method has been implemented in the “mcsqs” code of the Alloy Theoretic Automated Toolkit (ATAT) in the most general framework of multicomponent multisublattice systems and in a way that minimizes the amount of input information the user needs to specify and that allows for efficient parallelization.