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 & Galaxy. The organization has 8749 authors who have published 20843 publications receiving 795706 citations. The organization is also known as: UMBC.

Speech perception without hearing.

Abstract: In this study of visual phonetic speech perception without accompanying auditory speech stimuli, adults with normal hearing (NH;n=96) and with severely to profoundly impaired hearing (IH;n=72) identified consonant-vowel (CV) nonsense syllables and words in isolation and in sentences. The measures of phonetic perception were the proportion of phonemes correct and the proportion of transmitted feature information for CVs, the proportion of phonemes correct for words, and the proportion of phonemes correct and the amount of phoneme substitution entropy for sentences. The results demonstrated greater sensitivity to phonetic information in the IH group. Transmitted feature information was related to isolated word scores for the IH group, but not for the NH group. Phoneme errors in sentences were more systematic in the IH than in the NH group. Individual differences in phonetic perception for CVs were more highly associated with word and sentence performance for the IH than for the NH group. The results suggest that the necessity to perceive speech without hearing can be associated with enhanced visual phonetic perception in some individuals.

An overview of MODIS radiometric calibration and characterization

Abstract: The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the key instruments for NASA’s Earth Observing System (EOS), currently operating on both the Terra and Aqua satellites. The MODIS is a major advance over the previous generation of sensors in terms of its spectral, spatial, and temporal resolutions. It has 36 spectral bands: 20 reflective solar bands (RSB) with center wavelengths from 0.41 to 2.1 µm and 16 thermal emissive bands (TEB) with center wavelengths from 3.7 to 14.4 µm, making observations at three spatial resolutions: 250 m (bands 1–2), 500 m (bands 3–7), and 1km (bands 8–36). MODIS is a cross-track scanning radiometer with a wide field-of-view, providing a complete global coverage of the Earth in less than 2 days. Both Terra and Aqua MODIS went through extensive pre-launch calibration and characterization at various levels. In orbit, the calibration and characterization tasks are performed using its on-board calibrators (OBCs) that include a solar diffuser (SD) and a solar diffuser stability monitor (SDSM), a v-grooved flat panel blackbody (BB), and a spectro-radiometric calibration assembly (SRCA). In this paper, we present au overview of MODIS calibration and characterization activities, methodologies, and lessons learned from pre-launch characterization and in-orbit operation. Key issues discussed in this paper include in-orbit efforts of monitoring the noise characteristics of the detectors, tracking the solar diffuser and optics degradations, and updating the sensor’s response versus scan angle. The experiences and lessons learned through MODIS have played and will continue to play major roles in the design and characterization of future sensors.

People have shaped most of terrestrial nature for at least 12,000 years

Abstract: Archaeological and paleoecological evidence shows that by 10,000 BCE, all human societies employed varying degrees of ecologically transformative land use practices, including burning, hunting, species propagation, domestication, cultivation, and others that have left long-term legacies across the terrestrial biosphere. Yet, a lingering paradigm among natural scientists, conservationists, and policymakers is that human transformation of terrestrial nature is mostly recent and inherently destructive. Here, we use the most up-to-date, spatially explicit global reconstruction of historical human populations and land use to show that this paradigm is likely wrong. Even 12,000 y ago, nearly three quarters of Earth’s land was inhabited and therefore shaped by human societies, including more than 95% of temperate and 90% of tropical woodlands. Lands now characterized as “natural,” “intact,” and “wild” generally exhibit long histories of use, as do protected areas and Indigenous lands, and current global patterns of vertebrate species richness and key biodiversity areas are more strongly associated with past patterns of land use than with present ones in regional landscapes now characterized as natural. The current biodiversity crisis can seldom be explained by the loss of uninhabited wildlands, resulting instead from the appropriation, colonization, and intensifying use of the biodiverse cultural landscapes long shaped and sustained by prior societies. Recognizing this deep cultural connection with biodiversity will therefore be essential to resolve the crisis.

Dementia Care and Quality of Life in Assisted Living and Nursing Homes

Abstract: Purpose: There are few empirical studies relating components of long-term care to quality of life for residents with dementia. This study relates elements of dementia care in residential care/assisted living (RC/ AL) facilities and nursing homes to resident quality of life and considers the guidance this information provides for practice and policy. Design and Methods: We used a variety of report and observational measures of the structure and process of care and 11 standardized measures of quality of life to evaluate the care for and quality of life of 421 residents with dementia in 35 RC/AL facilities and 10 nursing homes in four states. Data were collected cross sectionally on-site, and we conducted a 6-month follow-up by telephone. Results: Change in quality of life was better in facilities that used a specialized worker approach, trained more staff in more domains central to dementia care, and encouraged activity participation. Residents perceived their quality of life as better when staff was more involved in care planning and when staff attitudes were more favorable. Better resident–staff communication was related to higher quality of life as observed and reported by care providers. Also, more stable resident–staff assignment was related to care providers’ lower quality-of-life ratings. Implications: Improvement in resident quality of life may be achieved by improved training and deployment of staff.

Skill in streamflow forecasts derived from large-scale estimates of soil moisture and snow

Abstract: In the American west, operational forecasts for spring–summer streamflow rely heavily on snow-water storage. Simulations with a suite of land-modelling systems suggest that snow-water storage generally contributes most to forecasting skill, but that the contribution of soil moisture is often significant, too. Seasonal predictions of streamflow can benefit from knowledge of the amounts of snow and other water present in a basin when the forecast is issued1,2,3,4,5. In the American west, operational forecasts for spring–summer streamflow rely heavily on snow-water storage and are often issued at the time of maximum snow accumulation. However, forecasts issued earlier can also show skill, particularly if proxy information for soil moisture, such as antecedent rainfall, is also used as a predictor1,4. Studies using multiple regression approaches and/or model-produced streamflows6,7,8,9 indeed suggest that information on soil moisture—a relatively underappreciated predictor—can improve streamflow predictions. Here, we quantify the relative contributions of early-season snow and soil moisture information to the skill of streamflow forecasts more directly and comprehensively: in a suite of land-modelling systems, we use the snow and soil moisture information both together and separately to derive seasonal forecasts. Our skill analysis reveals that early-season snow-water storage generally contributes most to skill, but the contribution of early-season soil moisture is often significant. In addition, we conclude that present-generation macroscale land-surface models forced with large-scale meteorological data can produce estimates of water storage in soils and as snow that are useful for basin-scale prediction.