University of Maryland, Baltimore County

About: University of Maryland, Baltimore County is a education organization based out in Baltimore, Maryland, United States. It is known for research contribution in the topics: Population & Aerosol. The organization has 8749 authors who have published 20843 publications receiving 795706 citations. The organization is also known as: UMBC.

SYBR Green I: Fluorescence Properties and Interaction with DNA

Abstract: In this study, we have investigated the fluorescence properties of SYBR Green I (SG) dye and its interaction with double-stranded DNA (dsDNA). SG/dsDNA complexes were studied using various spectroscopic techniques, including fluorescence resonance energy transfer and time-resolved fluorescence techniques. It is shown that SG quenching in the free state has an intrinsic intramolecular origin; thus, the observed >1,000-fold SG fluorescence enhancement in complex with DNA can be explained by a dampening of its intra-molecular motions. Analysis of the obtained SG/DNA binding isotherms in solutions of different ionic strength and of SG/DNA association in the presence of a DNA minor groove binder, Hoechst 33258, revealed multiple modes of interaction of SG inner groups with DNA. In addition to interaction within the DNA minor groove, both intercalation between base pairs and stabilization of the electrostatic SG/DNA complex contributed to increased SG affinity to double-stranded DNA. We show that both fluorescence and the excited state lifetime of SG dramatically increase in viscous solvents, demonstrating an approximate 200-fold enhancement in 100 % glycerol, compared to water, which also makes SG a prospective fluorescent viscosity probe. A proposed structural model of the SG/DNA complex is compared and discussed with results recently reported for the closely related PicoGreen chromophore.

The Black/White Disability Gap: Persistent Inequality in Later Life?

Abstract: Objectives. Previous research on differences between Black and White older adults has produced inconsistent results on whether a gap in disability exists and whether it persists over time. The present research identifies several reasons for the inconsistent results to date and examines Black/White differences in disability trajectories over 6 years. Methods. Data from the North Carolina Established Populations for the Epidemiologic Studies of the Elderly (1986‐ 1992) are used to estimate the disability gap and trajectory over time for both Black and White older adults. Results. Results indicate that a disability gap between Black and White adults exists, but after socioeconomic resources, social integration, and other health indicators are adjusted for, the trajectories of disability by race are not significantly different. Controlling for incident morbidity over time accounts for the significant difference in level of disability between the two groups. Discussion. This research supports the ‘‘persistent inequality’’ interpretation, indicating that Black adults have higher morbidity and disability earlier in life compared with White adults, and that the gap neither converges nor diverges over time.

Yahoo! as an ontology: using Yahoo! categories to describe documents

Abstract: We suggest that one (or a collection) of names of Yahoo! (or any other WWW indexer's) categories can be used to describe the content of a document. Such categories offer a standardized and universal way for referring to or describing the nature of real world objects, activities, documents and so on, and may be used (we suggest) to semantically characterize the content of documents. WWW indices, like Yahoo! provide a huge hierarchy of categories (topics) that touch every aspect of human endeavors. Such topics can be used as descriptors, similarly to the way librarians use for example, the Library of Congress cataloging system to annotate and categorize books.In the course of investigating this idea, we address the problem of automatic categorization of webpages in the Yahoo! directory. We use Telltale as our classifier; Telltale uses n-grams to compute the similarity between documents. We experiment with various types of descriptions for the Yahoo! categories and the webpages to be categorized. Our findings suggest that the best results occur when using the very brief descriptions of the Yahoo! categorized entries; these brief descriptions are provided either by the entries' submitters or by the Yahoo! human indexers and accompany most Yahoo!-indexed entries.

Weakly Supervised Cascaded Convolutional Networks

Abstract: Object detection is a challenging task in visual understanding domain, and even more so if the supervision is to be weak. Recently, few efforts to handle the task without expensive human annotations is established by promising deep neural network. A new architecture of cascaded networks is proposed to learn a convolutional neural network (CNN) under such conditions. We introduce two such architectures, with either two cascade stages or three which are trained in an end-to-end pipeline. The first stage of both architectures extracts best candidate of class specific region proposals by training a fully convolutional network. In the case of the three stage architecture, the middle stage provides object segmentation, using the output of the activation maps of first stage. The final stage of both architectures is a part of a convolutional neural network that performs multiple instance learning on proposals extracted in the previous stage(s). Our experiments on the PASCAL VOC 2007, 2010, 2012 and large scale object datasets, ILSVRC 2013, 2014 datasets show improvements in the areas of weakly-supervised object detection, classification and localization.

PARSIVEL Snow Observations: A Critical Assessment

Abstract: The performance of the laser-optical Particle Size Velocity (PARSIVEL) disdrometer is evaluated to determine the characteristics of falling snow. PARSIVEL’s measuring principle is reexamined to detect its limitations and pitfalls when applied to solid precipitation. This study uses snow observations taken during the Canadian Cloudsat/Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Validation Project (C3VP) campaign, when two PARSIVEL instruments were collocated with a single twodimensional disdrometer (2-DVD), which allows more detailed observation of snowflakes. When characterizing the snowflake size, PARSIVEL instruments inherently retrieve only one size parameter, which is approximately equal to the widest horizontal dimension (more accurately with large snowflakes) and that has no microphysical meaning. Unlike for raindrops, the equivolume PARSIVEL diameter—the PARSIVEL output variable—has no physical counterpart for snowflakes. PARSIVEL’s fall velocity measurement may not be accurate for a single snowflake particle. This is due to the internally assumed relationship between horizontal and vertical snow particle dimensions. The uncertainty originates from the shape-related factor, which tends to depart more and more from unity with increasing snowflake sizes and can produce large errors. When averaging over a large number of snowflakes, the correction factor is size dependent with a systematic tendency to an underestimation of the fall speed (but never exceeding 20%). Compared to a collocated 2-DVD for long-lasting events, PARSIVEL seems to overestimate the number of small snowflakes and large particles. The disagreement between PARSIVEL and 2-DVD snow measurements can only be partly ascribed to PARSIVEL intrinsic limitations (border effects and sizing problems), but it has to deal with the difficulties and drawbacks of both instruments in fully characterizing snow properties.