Search

Memory loss is a part of normative aging. Many older adults commonly forget to take prescribed medication, which can have an adverse effect on health. Therefore, it is important to provide older adults with a medication reminder service. There are several mobile apps and devices capable of reminding medication, but their user interfaces and operations are usually unfriendly to seniors. Considering the above demands and shortcomings, we proposed a conversation-based medication management system (CMMS). The CMMS uses a companion robot and the cloud to create medication reminders and check medication adherence. We implemented the CMMS in our ASCC (Advanced Sensing, Computation and Control) companion robot. To evaluate the CMMS, we tested our system through the mobile app end with 23 human subjects and the robot end with 15 human subjects. The feedback from the post-test survey shows that the convenience, usefulness and total rating of our system is 8.217, 8.696 and 8.478 out of 10 from the mobile app end and 9.000, 8.933 and 8.533 out of 10 from the robot end, respectively. The System Usability Scale (SUS) score of our system is 81.333 from the robot end users, which means the participants had a high satisfaction level when using the system.

Thorough comparison to observations is key to developing a credible climate model forecasting capability. Deep Space Climate Observatory (DSCOVR) measurements of Earth’s reflected solar and emitted thermal radiation provide a unique observational perspective that permits a more reliable model/data comparison than is possible with the otherwise available satellite data. The uniqueness is in the DSCOVR satellite’s viewing geometry, which enables continuous viewing of the Earth’s sunlit hemisphere from its Lissajous orbit around the Lagrangian L1 point. The key instrument is the Earth Polychromatic Imaging Camera (EPIC), which views the Earth’s sunlit hemisphere with 1024-by-1024-pixel imagery in 10 narrow spectral bands from 317 to 780 nm, acquiring up to 22 high spatial resolution images per day. The additional feature is that the frequency of EPIC image acquisition is nearly identical to that of the climate GCM data generation scheme where climate data for the entire globe are ‘instantaneously’ calculated at 1-h radiation time-step intervals. Implementation of the SHS (Sunlit Hemisphere Sampling) EPIC-view geometry for the in-line GCM output data sampling establishes a precise self-consistency in the space-time data sampling between EPIC observational and GCM output data generation and sampling. The remaining problem is that the GCM generated data are radiative fluxes, while the EPIC measurements are backscatter-dependent radiances. Radiance to flux conversion is a complex problem with no simple way to convert GCM radiative fluxes into spectral radiances. The more expedient approach is to convert the EPIC spectral radiances into broadband radiances by MODIS/CERES-based regression relationships and then into solar radiative fluxes using the CERES angular distribution models. Averaging over the sunlit hemisphere suppresses the meteorological weather noise, but preserves the intra-seasonal larger scale variability. Longitudinal slicing by the Earth’s rotation permits a self-consistent model/data comparison of the longitudinal model/data differences in the variability of the reflected solar radiation. Ancillary EPIC Composite data provide additional cloud property information for climate model diagnostics. Comparison of EPIC-derived seasonal and longitudinal variability of the Earth’s planetary albedo with the GISS ModelE2 results shows systematic overestimate of cloud reflectivity over the Pacific Ocean with corresponding underestimates over continental land areas.

Recent studies have emphasized the changes in large-scale brain networks related to healthy aging, with the ultimate purpose to aid in differentiating normal neurocognitive aging from neurodegenerative disorders that also arise with age. Emerging evidence from functional Magnetic Resonance Imaging (fMRI) indicates that connectivity patterns within specific brain networks, especially the Default Mode Network (DMN), distinguish those with Alzheimer's disease from healthy individuals. In addition, disruptive alterations in the large-scale brain systems that support high-level cognition are shown to accompany cognitive decline at the behavioral level, which is commonly observed in the aging populations, even in the absence of disease. Although fMRI is useful for assessing functional changes in brain networks, its high costs and limited accessibility discourage studies that need large populations. In this study, we investigated the aging-effect on large-scale networks of the human brain using high-density electroencephalography and electrophysiological source imaging, which is a less costly and more accessible alternative to fMRI. In particular, our study examined a group of healthy subjects in the age range from middle- to older-aged adults, which is an under-studied range in the literature. Employing a high-resolution computation model, our results revealed age associations in the connectivity pattern of DMN in a consistent manner with previous fMRI findings. Particularly, in combination with a standard battery of cognitive tests, our data showed that in the posterior cingulate / precuneus area of DMN higher brain connectivity was associated with lower performance on an episodic memory task. The findings demonstrate the feasibility of using electrophysiological imaging to characterize large-scale brain networks and suggest that changes in network connectivity are associated with normal aging.

Recently, functional near-infrared spectroscopy (fNIRS) has been utilized to image the hemodynamic activities and connectivity in the human brain. With the advantage of economic efficiency, portability, and fewer physical constraints, fNIRS enables studying of the human brain at versatile environment and various body positions, including at bed side and during exercise, which complements the use of functional magnetic resonance imaging (fMRI). However, like fMRI, fNIRS imaging can be influenced by the presence of a strong global component. Yet, the nature of the global signal in fNIRS has not been established. In this study, we investigated the relationship between fNIRS global signal and electroencephalogram (EEG) vigilance using simultaneous recordings in resting healthy subjects in high-density and whole-head montage. In Experiment 1, data were acquired at supine, sitting, and standing positions. Results found that the factor of body positions significantly affected the amplitude of the resting-state fNIRS global signal, prominently in the frequency range of 0.05–0.1 Hz but not in the very low frequency range of less than 0.05 Hz. As a control, the task-induced fNIRS or EEG responses to auditory stimuli did not differ across body positions. However, EEG vigilance plays a modulatory role in the fNIRS signals in the frequency range of less than 0.05 Hz: resting-state sessions of low EEG vigilance measures are associated with high amplitudes of fNIRS global signals. Moreover, in Experiment 2, we further examined the epoch-to-epoch fluctuations in concurrent fNIRS and EEG data acquired from a separate group of subjects and found a negative temporal correlation between EEG vigilance measures and fNIRS global signal amplitudes. Our study for the first time revealed that vigilance as a neurophysiological factor modulates the resting-state dynamics of fNIRS, which have important implications for understanding and processing the noises in fNIRS signals.

Various space-based sensors have been designed and corresponding algorithms developed to retrieve aerosol optical depth (AOD), the very basic aerosol optical property, yet considerable disagreement still exists across these different satellite data sets. Surface-based observations aim to provide ground truth for validating satellite data; hence, their deployment locations should preferably contain as much spatial information as possible, i.e., high spatial representativeness. Using a novel Ensemble Kalman Filter (EnKF)-based approach, we objectively evaluate the spatial representativeness of current Aerosol Robotic Network (AERONET) sites. Multisensor monthly mean AOD data sets from Moderate Resolution Imaging Spectroradiometer, Multiangle Imaging Spectroradiometer, Sea-viewing Wide Field-of-view Sensor, Ozone Monitoring Instrument, and Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar are combined into a 605-member ensemble, and AERONET data are considered as the observations to be assimilated into this ensemble using the EnKF. The assessment is made by comparing the analysis error variance (that has been constrained by ground-based measurements), with the background error variance (based on satellite data alone). Results show that the total uncertainty is reduced by ~27% on average and could reach above 50% over certain places. The uncertainty reduction pattern also has distinct seasonal patterns, corresponding to the spatial distribution of seasonally varying aerosol types, such as dust in the spring for Northern Hemisphere and biomass burning in the fall for Southern Hemisphere. Dust and biomass burning sites have the highest spatial representativeness, rural and oceanic sites can also represent moderate spatial information, whereas the representativeness of urban sites is relatively localized. A spatial score ranging from 1 to 3 is assigned to each AERONET site based on the uncertainty reduction, indicating its representativeness level.

Surface remote sensing of aerosol properties provides “ground truth” for satellite and model validation, and is an important component of aerosol observation system. Due to the different characteristics of background aerosol variability, information obtained at different locations usually have different spatial representativeness, implying that the location should be carefully chosen so that its measurement could be extended to a greater area. In this study, we present an objective observation array design technique that automatically determines the optimal locations with the highest spatial representativeness based on the Ensemble Kalman Filter (EnKF) theory. The ensemble is constructed using aerosol optical depth (AOD) products from five satellite sensors. The optimal locations are solved sequentially by minimizing the total analysis error variance, which means that observations at these locations will reduce the background error variance to the largest extent. The location determined by the algorithm is further verified to have larger spatial representativeness than some other arbitrary location. In addition to the existing active AERONET sites, the 40 selected optimal locations are mostly concentrated on regions with both high AOD inhomogeneity and its spatial representativeness, namely the Sahel, South Africa, East Asia and North Pacific Islands. These places should be the focuses of establishing future AERONET sites in order to further reduce the uncertainty in the monthly mean AOD. Observations at these locations contribute to approximately 50% of the total background uncertainty reduction.

The current study examined relationships between laterality in cerebral oxygenation (L-COX), sleep-disordered breathing (SDB), and daytime function in 16 adults with mild cognitive impairment (MCI). All participants underwent two nights of diagnostic polysomnography. Using dual-cerebral oximetry, L-COX was defined by differences ≥4% in right- versus left-sided percent cerebral oxyhemoglobin saturation. Eight patients had SDB. L-COX was found in five patients, but only on nights with SDB. Greater L-COX was associated more severe SDB: higher frequency of apneas + hypopneas per hour ( r = 0.66, p < 0.01), desaturations per hour ( r = 0.73, p < 0.01), and percent time with oxygen saturation r = 0.65, p < 0.01). Greater laterality, but not severity of SDB, was associated with poorer functional ability (Lawton Instrumental Activities of Daily Living Scale: r = −0.83, p = 0.02), lower cognitive function (Mini-Mental State Examination: r = −0.76, p = 0.03), and greater daytime sleepiness (Epworth Sleepiness Scale: r = 0.85, p < 0.001). L-COX associated with SDB suggests disruptions in cerebral autoregulation and need for aggressive treatment of SDB in individuals with MCI. [Res Gerontol Nurs. 2018; 11(6):282–292.]

Surface remote sensing of aerosol properties provides "ground truth" for satellite and model validation, and is an important component of aerosol observation system. Due to the different characteristics of background aerosol variability, information obtained at different locations usually have different spatial representativeness, implying that the location should be carefully chosen so that its measurement could be extended to a greater area. In this study, we present an objective observation array design technique that automatically determines the optimal locations with the highest spatial representativeness based on the Ensemble Kalman Filter (EnKF) theory. The ensemble is constructed using aerosol optical depth (AOD) products from five satellite sensors. The optimal locations are solved sequentially by minimizing the total analysis error variance, which means that observations at these locations will reduce the background error variance to the largest extent. The location determined by the algorithm is further verified to have larger spatial representativeness than some other arbitrary location. In addition to the existing active AERONET sites, the 40 selected optimal locations are mostly concentrated on regions with both high AOD inhomogeneity and its spatial representativeness, namely the Sahel, South Africa, East Asia and North Pacific Islands. These places should be the focuses of establishing future AERONET sites in order to further reduce the uncertainty in the monthly mean AOD. Observations at these locations contribute to approximately 50% of the total background uncertainty reduction.

Background: Cognitive complaints (“chemo brain”) are reported frequently after breast cancer treatment but little is known about its incidence and causes. Before we can intervene we need to be able to diagnose it properly. Mini Mental state examination (MMSE) can detect advanced Alzheimer's but won't help in detecting mild cognitive disturbances. We used Montreal Cognitive Assessment for Telephone (MoCA-T) and full scale Montreal Cognitive Assessment for Telephone (MoCA) to diagnose mild cognitive impairments in patients having normal MMSE. Methods: 20 breast cancer survivors aged 50 years or older completed MoCA-T and MoCA, a year after they completed their treatment for breast cancer, describing the impact of their treatment regimen on their short term memory and ability to think and concentrate. On Day 5, they underwent a standardized laboratory protocol that assessed both behavioral and electroencephalographic (EEG) indicators of memory consolidation. Results: Patient characteristics: 20 postmenopausal breast cancer survivors aged 50 or above participated in the study a year after they completed their therapy. We are reporting preliminary results of 10 patients. Patients had stage I-III disease (stage I – One patient, Stage II – five patients, and stage III- four patients). All of them received various chemo regimens e.g. Cytoxan, methotrexate, 5-FU (CMF), Taxol, Trastuzumab (TH), Adriamycin (AC), taxotere, carboplatin (TCH). 8/10 patients received adjuvant radiation. 1/10 patient underwent reconstruction later. 7/10 patients received hormonal therapy with aromatase inhibitors. Results of MoCA –T and MoCA: MoCA-T, tests attention and concentration, executive functions, memory, language, conceptual thinking, calculations, and orientation. Possible scores range from 0-22 and scores 26 is normal but 5/10 patients had abnormal MoCA and 3/10 patients had impaired MoCA-T signifying that almost 50%patients develop mild cognitive impairment after breast cancer treatment. During memory consolidation, EEG contained less theta and frequent bursts of alpha waves which is commonly seen in patients with neuropathic pain and insomnia. MoCA-T and MoCA results for the patientsPatient no.MoCA-TMoCAPtient 00817*23*Patient 0102126Patient 0111923*Patient 01216*27Patient 0132027Patient 01517*21*Patient 0161824*Patient 0172025*Patient 0191926Patient 0202129*presents affected patient Conclusions: The study signifies that mild cognitive impairment from breast cancer treatment (or “chemo brain”) was frequently reported and MoCA-T and MoCA tests were able to show even mild cognitive impairment in these patients. We are compiling our full data for EEG but the early results show that the patients had less theta but had frequent bursts of alpha waves, a pattern seen commonly in patients with insomnia and neuropathic pain. They retain fewer items and take more time responding to items as compared to normal people. We need more studies to diagnose and treat mild cognitive impairment (“chemo brain”) in breast survivors as most of these patients are still working and can be a valuable part of the community. Citation Format: Razaq WA, Tanaka T, Carlson B, Wenger M, Friedman J, Benbrook D, Craft M. Diagnosing cognitive impairment (“chemo brain”) in breast cancer survivors [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P4-20-09.

Objectives To examine the association between performance-based neurocognitive and patient-reported cognitive function tests and identify characteristics that may explain observed discrepancies as a means to advance intervention development. Sample & setting 40 adults diagnosed with a primary brain tumor (PBT) (high-grade, n = 35) were recruited from two academic neuro-oncology clinics in North Carolina. Methods & variables Eligibility included a Mini-Mental State Examination score of 24 or greater, having completed cancer treatment, and having tumor stability. Participants completed performance-based neurocognitive and patient-reported cognitive function, demographic, and symptom assessment tests at one time point. Results Neurocognitive impairments included executive control, memory, and attention. Age, time since diagnosis, and tumor- or treatment-specific variables were not associated with neurocognitive or patient-reported cognitive function. Those reporting worse cognitive impairment tended also to report greater severity of PBT-specific and depressive symptoms. Implications for nursing Patient-reported cognitive concerns warrant additional assessment for potential interventions to maintain function.

The epigraph in poet Jean Valentine's book Break the Glass: "A pencil/for a wing bone" (by Lorine Neidecker) leads us to consider the way writing allows for transcendence. Similarly, in her work, Meta Kušar brushes out stars with a comb and then finds "an accomplice/combed/in this hollowed-out place". From the two countries US and Slovenia of such vastly different sizes, these poets, both influenced by such luminaries as Emily Dickinson and Marina Tsvetaeva, have carved out intimate spiritually enriching spaces where consciousness meets the sublime. Focusing on Kušar's view of Heraclitus as a teacher who "understood invisible strings are stronger than visible ones," I will explore the thematic, literary and stylistic connections between these two literary stars, as well as some of their differences in how they cultivate a poetics of the invisible that illuminates the mysterious underworld of the human soul as it negotiates the political, philosophical and ethical realms of contemporary existence. Epigraf "A pencil/for a wing bone" (Svinčnik / za lopatico) v pesniški zbirki Break the Glass pesnice Jean Valentine (gre za verz Lorine Neidecker) spodbuja k razmisleku o tem, kako pisanje omogoča transcendenco. Podobno v svojem delu Meta Kušar razčeše zvezde z glavnikom in nato najde "zaveznika / počesanega / v tej votli deželi". Pesnici, ki prihajata iz dveh po velikosti tako različnih držav, kot sta ZDA in Slovenija, in na kateri so vplivale zvezdnice, kot sta Emily Dickinson in Marina Cvetajeva, sta ustvarili intimne in duhovno oplajajoče prostore, v katerih se zavest sreča s sublimnostjo. Avtorica se osredotoča na pogled Kušarjeve, da je Heraklit učitelj, ki "je razumel, da so nevidne vezi močnejše od vidnih", ter proučuje tematske, literarne in slogovne povezave med tema dvema literarnima zvezdama, pa tudi nekatere razlike pri ustvarjanju poetike nevidnega, ki osvetljuje skrivnostno podzemlje človeške duše med obvladovanjem politične, filozofske in etične sfere sodobnega obstoja.

Various space-based sensors have been designed and corresponding algorithms developed to retrieve aerosol optical depth (AOD), the very basic aerosol optical property, yet considerable disagreement still exists across these different satellite data sets. Surface-based observations aim to provide ground truth for validating satellite data; hence, their deployment locations should preferably contain as much spatial information as possible, i.e., high spatial representativeness. Using a novel Ensemble Kalman Filter (EnKF)- based approach, we objectively evaluate the spatial representativeness of current Aerosol Robotic Network (AERONET) sites. Multisensor monthly mean AOD data sets from Moderate Resolution Imaging Spectroradiometer, Multiangle Imaging Spectroradiometer, Sea-viewing Wide Field-of-view Sensor, Ozone Monitoring Instrument, and Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar are combined into a 605-member ensemble, and AERONET data are considered as the observations to be assimilated into this ensemble using the EnKF. The assessment is made by comparing the analysis error variance (that has been constrained by ground-based measurements), with the background error variance (based on satellite data alone). Results show that the total uncertainty is reduced by approximately 27% on average and could reach above 50% over certain places. The uncertainty reduction pattern also has distinct seasonal patterns, corresponding to the spatial distribution of seasonally varying aerosol types, such as dust in the spring for Northern Hemisphere and biomass burning in the fall for Southern Hemisphere. Dust and biomass burning sites have the highest spatial representativeness, rural and oceanic sites can also represent moderate spatial information, whereas the representativeness of urban sites is relatively localized. A spatial score ranging from 1 to 3 is assigned to each AERONET site based on the uncertainty reduction, indicating its representativeness level.

Chemotherapy destroys cells indiscriminantly and releases proinflammatory factors into the bloodstream that can adhere to endothelial cells (ECs); resulting in phenotypical changes consistent with “accelerated vascular aging”. This pilot study examined associations between markers of EC integrity, vascular aging, and cognition in 15 female breast cancer survivors 12–18 months after chemotherapy (median age: 57 years) and 2 non-cancer controls (58/59 years). EC integrity was evaluated using frequency-dependent electrical impedance (Z4000Hz) and levels of apoptosis (caspase-3/7), inflammation (NFkB activation), and oxidative stress (NRF2 activation) in cultured human endothelial cells (EC) exposed to the subject’s serum. Vascular aging was characterized by low serum insulin growth factor ([IGF1a]

Because of the importance of clouds in modulating Earth’s energy budget, it is critical to understand their variability in space and time for climate and modeling studies. This study examines the consistency of the spatiotemporal variability of cloud amount (CA) and cloud-top pressure (CTP) represented by five 7-yr satellite datasets from the Global Energy and Water Cycle Experiment (GEWEX) cloud assessment project, and total cloud fraction observation from the Extended Edited Cloud Reports Archive (EECRA). Two spectral analysis techniques, namely combined maximum covariance analysis (CMCA) and combined principal component analysis (CPCA), are used to extract the dominant modes of variability from the combined datasets, and the resulting spatial patterns are compared in parallel. The results indicate that the datasets achieve overall excellent agreement on both seasonal and interannual scales of variability, with the correlations between the spatial patterns mostly above 0.6 and often above 0.8. For seasonal variability, the largest differences are found in the Northern Hemisphere high latitudes and near the South African coast for CA and in the Sahel region for CTP, where some differences in the phase and strength of the seasonal cycle are found. On interannual scales, global cloud variability is mostly associated with major climate modes, including El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), and the Indian Ocean dipole mode (IODM), and the datasets also agree reasonably well. The good agreement across the datasets supports the conclusion that they are describing cloud variations with these climate modes.

Spectral dependence of aerosol single-scattering albedo (SSA) has been used to infer aerosol composition. In particular, aerosol mixtures dominated by dust absorption will have monotonically increasing SSA with wavelength while that dominated by black carbon absorption has monotonically decreasing SSA spectra. However, by analyzing SSA measured at four wavelengths, 440, 675, 870, and 1020 nm from the Aerosol Robotic Network data set, we find that the SSA spectra over East Asia are frequently peaked at 675 nm. In these cases, we suggest that SSA spectral curvature, defined as the negative of the second derivative of SSA as a function of wavelength, can provide additional information on the composition of these aerosol mixtures. Aerosol SSA spectral curvatures for East Asia during fall and winter are considerably larger than those found in places primarily dominated by biomass burning or dust aerosols. SSA curvature is found to increase as the SSA magnitude decreases. The curvature increases with coarse mode fraction (CMF) to a CMF value of about 0.4, then slightly decreases or remains constant at larger CMF. Mie calculations further verify that the strongest SSA curvature occurs at approx. 40% dust fraction, with 10% scattering aerosol fraction. The nonmonotonic SSA spectral dependence is likely associated with enhanced absorption in the shortwave by dust, absorption by black carbon at longer wavelengths, and also the flattened absorption optical depth spectral dependence due to the increased particle size.

Due to their extensive spatial coverage, satellite Aerosol Optical Depth (AOD) observations have been widely used to estimate and predict surface PM2.5 concentrations. While most previous studies have focused on establishing relationships between collocated, hourly or daily AOD and PM2.5 measurements, in this study, we instead focus on the comparison of the large-scale spatial and temporal variability between satellite AOD and PM2.5 using monthly mean measurements. A newly developed spectral analysis technique e Combined Maximum Covariance Analysis (CMCA) is applied to Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging Spectroradiometer (MISR), Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Ozone Monitoring Instrument (OMI) AOD datasets and Environmental Protection Agency (EPA) PM2.5 data, in order to extract and compare the dominant modes of variability. Results indicate that AOD and PM2.5 agree well in terms of interannual variability. An overall decrease is found in both AOD and PM2.5 across the United States, with the strongest signal over the eastern US. With respect to seasonality, good agreement is found only for Eastern US, while for Central and Western US, AOD and PM2.5 seasonal cycles are largely different or even reversed. These results are verified using Aerosol Robotic Network (AERONET) AOD observations and differences between satellite and AERONET are also examined. MODIS and MISR appear to have the best agreement with AERONET. In order to explain the disagreement between AOD and PM2.5 seasonality, we further use Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) extinction profile data to investigate the effect of two possible contributing factors, namely aerosol vertical distribution and cloud-free sampling. We find that seasonal changes in aerosol vertical distribution, due to the seasonally varying mixing height, is the primary cause for the AOD and PM2.5 seasonal discrepancy, in particular, the low AOD but high PM2.5 observed during the winter season for Central and Western US. In addition, cloud-free sampling by passive sensors also induces some bias in AOD seasonality, especially for the Western US, where the largest seasonal change in cloud fraction is found. The seasonal agreement between low level (below 500 m AGL), all sky CALIOP AOD and PM2.5 is significantly better than column AOD from MODIS, MISR, SeaWiFS and OMI. In particular, the correlation between low level, all sky AOD and PM2.5 seasonal cycles increases to above 0.7 for Central and Western US, as opposed to near zero or negative correlation for column, clear sky AOD. This result highlights the importance of accounting for the seasonally varying aerosol profiles and cloud-free sampling bias when using column AOD measurements to infer surface PM2.5 concentrations.

Advances in breast cancer treatment have markedly increased survivorship over the past three decades, with over 3.1 million survivors expected to live into their 70s and 80s. Without symptom relief interventions, nearly 35% of these survivors will have life-altering and distressing cognitive symptoms. This pilot study explored associations between serum markers of vascular aging, laterality in cerebral oxygenation, and severity of cognitive impairment in women, 12-18 months after chemotherapy for stage 2/3 invasive ductal breast cancer. Fifteen women (52-84 years) underwent a brief cognitive assessment (Montreal Cognitive Assessment [MOCA]) and blood draws to assess markers of vascular aging (interleukin-6 [IL-6], tumor necrosis factor alpha [TNF-α], C-reactive protein [CRP], and insulin growth factor-1 [IGF-1]). All underwent a computer-based test protocol that is known to increase blood flow within the frontal lobes. Percent cerebral oxyhemoglobin saturation (rcSO2) was recorded during and after testing. Laterality in rcSO2 was defined by ≥ 3% difference between left and right rcSO2 (|rcSO2 meanRIGHT - meanLEFT|). Eight participants had MOCA scores between 21 and 25 points, suggestive of mild cognitive impairment. Neither CRP (r = -.24) nor IL-6 (r = .34) nor TNF-α (r = .002) were associated with MOCA scores. Higher IL-6 was associated with greater laterality (r = .41). MOCA scores were significantly lower in subjects with laterality in rcSO2 than in those without laterality (F(1,14) = 13.5, p = 003). Lower IGF-1 was significantly associated with greater laterality (r = - .66, p = .007) and lower cognitive function (r = .58). These findings suggest that persistent cognitive impairment is associated with phenotypical changes consistent with accelerated vascular aging.

Amnestic Mild Cognitive Impairment (aMCI), a condition in which the memory functions of cognition are significantly impaired, is an established risk factor for Alzheimer's disease. Electroencephalography (EEG) is a tool capable of measuring the dynamics of the brain's neural networks, and is thus an important means in analysis and understanding of aMCI. In this proof-of-concept study, we compared the brain activation patterns of ten aMCI subjects with those of four healthy subjects during sleep by employing a 64-channel EEG data collection system. The power spectrum was analyzed to identify sleep stages, while spectral topography and source imaging techniques were employed to study the fluctuating patterns of the brain. Results of this study show an increase in activation power across all sleep stages in the delta and theta frequency bands alongside a decrease in alpha band activity for aMCI subjects. Source imaging analysis of the resting EEG identified default mode network, which becomes decoupled as sleep stages deepen. In the proof-of-concept study, our exploratory analysis demonstrated the feasibility of imaging dynamic network organization using EEG in aMCI.

Federal funding from the Child Care and Development Fund (CCDF) enables states to offset the cost of child care for eligible low-income families to support parental employment and promote healthy child development. The federal government sets a benchmark for provider payment rates in order to ensure that low-income families have access to child care settings comparable to those available to non-CCDF families. In order to meet this “equal access” objective, states need reliable information and valid methods to estimate benchmark prices in local child care markets. Although all 50 states face the challenge of meeting the federal benchmark, limited research on best practices is available to guide them. This case study of Colorado's child care market prices highlights key challenges to states in using survey data to set provider payment rates, offering policy and practice implications for sampling, collecting price data, and estimating valid child care benchmark prices.

Nocturia is a bothersome symptom that increases with age, resulting in sleep disruption, an increased risk of falls, and a greater likelihood of rating one's health as poor. It is often a symptom of conditions that cause low volume voiding, overproduction of urine across the day or only at night and a symptom of a sleep disorder. Nocturia affects quality of life and has an impact on aging in place, thus assessment and treatment are essential. Behavioral treatments should be explored first, keeping in mind what the affected older adult defines as the desired outcomes of treatment.

Satellite measurements of global aerosol properties are very useful in constraining aerosol parameterization in climate models. The reliability of different data sets in representing global and regional aerosol variability becomes an essential question. In this study, we present the results of a comparison using combined principal component analysis (CPCA), applied to monthly mean, mapped (Level 3) aerosol optical depth (AOD) product from Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Ozone Monitoring Instrument (OMI). This technique effectively finds the common space-time variability in the multiple data sets by decomposing the combined AOD field. The results suggest that all of the sensors capture the globally important aerosol regimes, including dust, biomass burning, pollution, and mixed aerosol types. Nonetheless, differences are also noted. Specifically, compared with MISR and OMI, MODIS variability is significantly higher over South America, India, and the Sahel. MODIS deep blue AOD has a lower seasonal variability in North Africa, accompanied by a decreasing trend that is not found in either MISR or OMI AOD data. The narrow swath of MISR results in an underestimation of dust variability over the Taklamakan Desert. The MISR AOD data also exhibit overall lower variability in South America and the Sahel. OMI does not capture the Russian wild fire in 2010 nor the phase shift in biomass burning over East South America compared to Central South America, likely due to cloud contamination and the OMI row anomaly. OMI also indicates a much stronger (boreal) winter peak in South Africa compared with MODIS and MISR.

Moderate Resolution Imaging SpectroRadiometer (MODIS) and Multi-angle Imaging Spectroradiomater (MISR) provide regular aerosol observations with global coverage. It is essential to examine the coherency between space- and ground-measured aerosol parameters in representing aerosol spatial and temporal variability, especially in the climate forcing and model validation context. In this paper, we introduce Maximum Covariance Analysis (MCA), also known as Singular Value Decomposition analysis as an effective way to compare correlated aerosol spatial and temporal patterns between satellite measurements and AERONET data. This technique not only successfully extracts the variability of major aerosol regimes but also allows the simultaneous examination of the aerosol variability both spatially and temporally. More importantly, it well accommodates the sparsely distributed AERONET data, for which other spectral decomposition methods, such as Principal Component Analysis, do not yield satisfactory results. The comparison shows overall good agreement between MODIS/MISR and AERONET AOD variability. The correlations between the first three modes of MCA results for both MODIS/AERONET and MISR/ AERONET are above 0.8 for the full data set and above 0.75 for the AOD anomaly data. The correlations between MODIS and MISR modes are also quite high (greater than 0.9). We also examine the extent of spatial agreement between satellite and AERONET AOD data at the selected stations. Some sites with disagreements in the MCA results, such as Kanpur, also have low spatial coherency. This should be associated partly with high AOD spatial variability and partly with uncertainties in satellite retrievals due to the seasonally varying aerosol types and surface properties.

Many remote sensing techniques and passive sensors have been developed to measure global aerosol properties. While instantaneous comparisons between pixel-level data often reveal quantitative differences, here we use Empirical Orthogonal Function (EOF) analysis, also known as Principal Component Analysis, to demonstrate that satellite-derived aerosol optical depth (AOD) data sets exhibit essentially the same spatial and temporal variability and are thus suitable for large-scale studies. Analysis results show that the first four EOF modes of AOD account for the bulk of the variance and agree well across the four data sets used in this study (i.e., Aqua MODIS, Terra MODIS, MISR, and SeaWiFS). Only SeaWiFS data over land have slightly different EOF patterns. Globally, the first two EOF modes show annual cycles and are mainly related to Sahara dust in the northern hemisphere and biomass burning in the southern hemisphere, respectively. After removing the mean seasonal cycle from the data, major aerosol sources, including biomass burning in South America and dust in West Africa, are revealed in the dominant modes due to the different interannual variability of aerosol emissions. The enhancement of biomass burning associated with El Nino over Indonesia and central South America is also captured with the EOF technique.

The nominal Global Aerosol Climatology Project (GACP) record of aerosol optical thickness (AOT) and Angstrom exponent (AE) over the oceans is extended by 6 months to cover the period from August 1981 through December 2005. The most recent 4-year segment reveals no significant short-term tendencies in globally and hemispherically averaged AOTs and AEs. This finding is consistent with contemporaneous MODIS and MISR results and the accumulating evidence of a gradual transition from global brightening to global dimming. We also analyze the retrieval implications of allowing the imaginary part of the aerosols refractive index Im( m ) to change over the duration of the GACP record. Our sensitivity study shows that increasing Im( m ) from 0.003 during the 4-year pre-Pinatubo period up to 0.007 during the most recent 4-year segment of GACP data eliminates the previously identified long-term decreasing AOT trend. Should this long-term trend in Im( m ) be real then it would cause the global absorption AOT over the oceans to more than double and the global single-scattering albedo to decrease from ∼0.95 to ∼0.88. Such changes could make tropospheric aerosols significant contributors to the recent surface temperature increase.

The dominant interannual El Niño–Southern Oscillation (ENSO) phenomenon and the short length of climate observation records make it difficult to study long-term climate variations in the spatiotemporal domain. Based on the fact that the ENSO signal spreads to remote regions and induces delayed climate variation through atmospheric teleconnections, an ENSO-removal method is developed through which the ENSO signal can be approximately removed at the grid box level from the spatiotemporal field of a climate parameter. After this signal is removed, long-term climate variations are isolated at mid- and low latitudes in the climate parameter fields from observed and reanalysis datasets. This paper addresses the long-term global warming trend (GW); a companion paper concentrates on Pacific pan-decadal variability (PDV). The warming that occurs in the Pacific basin (approximately 0.4 K in the twentieth century) is much weaker than in surrounding regions and the other two ocean basins (approximately 0.8 K). The modest warming in the Pacific basin is likely due to its dynamic nature on the interannual and decadal time scales and/or the leakage of upper ocean water through the Indonesian Throughflow. Based on the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) and the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40), a comprehensive atmospheric structure associated with the GW trend is given. Significant discrepancies exist between the two datasets, especially in the tightly coupled dynamics and water vapor fields. The dynamics fields based on NCEP–NCAR, which show a change in the Walker Circulation, are consistent with the GW change in the surface temperature field. However, intensification in the Hadley Circulation is associated with GW trend in ERA-40 instead.

The spatiotemporal structure of Pacific pan-decadal variability (PDV) is isolated in global long-term surface temperature (ST) datasets and reanalysis atmospheric parameter fields from which El Niño–Southern Oscillation (ENSO) effects have been removed. Empirical orthogonal function (EOF) and combined EOF analysis of the resulting time series identify PDV as one of two primary modes of long-term variability, the other being a global warming (GW) trend, which is addressed in a companion paper (Part I). In this study, it is shown that one of several PDV interdecadal regime shifts occurred during the 1990s. This significant change in the Pacific basin is comparable but antiphase to the well-known 1976 climate regime shift and is consistent with the observed changes in biosystems and ocean circulation. A comprehensive picture of PDV as manifested in the troposphere and at the surface is described. In general, the PDV spatial patterns in different parameter fields share some similarities with the patterns associated with ENSO, but important differences exist. First, the PDV circulation pattern is shifted westward by about 20° and is less zonally extended than that for ENSO. The westward shift of the PDV wave train produces a different North American teleconnection pattern that is more west–east oriented. The lack of a strong PDV surface temperature (ST) signal in the west equatorial Pacific and the relatively strong ST signal in the subtropical regions are consistent with an atmospheric overturning circulation response that differs from the one associated with ENSO. The analysis also suggests that PDV is a combination of decadal and/or interdecadal oscillations interacting through teleconnections.

OBJECTIVES: To explore differences in cerebral oxygen reserves during sleep in old and young adults. DESIGN: Descriptive cross-sectional study. SETTING: General clinical research center. PARTICIPANTS: Nine old (aged 65–84) and 10 young (aged 21–39) adults. MEASUREMENTS: Subjects were monitored during the first nightly sleep cycle using standard polysomnography, including measures of arterial oxyhemoglobin saturation (SaO2). Changes in regional cerebral oxyhemoglobin saturation (rcSO2) were used to estimate cerebral oxygen reserves. General linear models were used to test group differences in the change in SaO2 and rcSO2 during sleep.

A number of passive satellite instruments have been used to develop global climatologies of terrestrial tropospheric aerosols by analyzing the properties of sunlight reflected by the atmosphere–surface system. The outcome of these efforts are several climatologies which all purport to represent the same aerosol characteristics such as optical thickness and size. However, the quantitative differences between these climatologies have been found to far exceed the corresponding individual uncertainty claims. The magnitude of these differences is alarming and necessitates a detailed critical assessment and integrated analysis that would go far beyond simple intercomparisons of various satellite products and comparisons of satellite aerosol optical thickness results with ground-based sun-photometer data. This paper outlines the framework for a global long-term satellite climatology of aerosol properties based on a consistent combination of previous, current, and near-future satellite retrievals. We also discuss potential future strategies for deriving a much improved aerosol climatology from Earth-orbiting satellites.

The aim of this exploratory study was to examine the relationship of electroencephalogram (EEG) arousals to breathing patterns and the relationship of both arousals and breathing patterns to arterial oxygenation during sleep in older adults. Five older adults were monitored using standard polysomnography. Records were divided into 5-min segments and breathing patterns identified based on the level of respiratory periodicity and the variability in the frequency of breathing cycles. Standard criteria were used to determine sleep states and occurrence of EEG arousals. High respiratory periodicity was seen in 23% of the segments, whereas 24% had low respiratory periodicity with minimal variability in the frequency of breathing (Type A low respiratory periodicity) and 53% had low respiratory periodicity with high variability in the frequency of breathing (Type B low respiratory periodicity). Nearly all (97%) segments with high respiratory periodicity had EEG arousals, whereas fewer segments (33%) with low respiratory periodicity had arousals, regardless of the stage of sleep. Desaturations occurred more often in segments with high respiratory periodicity, F (2,4) = 57.3, p < .001, but overall, the mean SaO2 of segments with high respiratory periodicity did not differ from levels seen in segments with low respiratory periodicity, F( 2,4) = 0.77, ns. Our findings suggest that high respiratory periodicity is a common feature of EEG arousals and, in older adults, may be important for maintaining oxygen levels during desaturations during sleep.

In this study, we model single-scattering properties of small cirrus crystals using mixtures of polydisperse, randomly oriented spheroids and cylinders with varying aspect ratios and with a refractive index representative of water ice at a wavelength of 1.88 μm. The Stokes scattering matrix elements averaged over wide shape distributions of spheroids and cylinders are compared with those computed for polydisperse surface-equivalent spheres. The shape-averaged phase function for a mixture of oblate and prolate spheroids is smooth, featureless, and nearly flat at side-scattering angles and closely resembles those typically measured for cirrus. Compared with the ensemble-averaged phase function for spheroids, that for a shape distribution of cylinders shows a relatively deeper minimum at side-scattering angles. This may indicate that light scattering from realistic cirrus crystals can be better represented by a shape mixture of ice spheroids. Interestingly, the single-scattering properties of shape-averaged oblate and prolate cylinders are very similar to those of compact cylinders with a diameter-to-length ratio of unity. The differences in the optical cross sections, single-scattering albedo, and asymmetry parameter between the spherical and the nonspherical particles studied appear to be relatively small. This may suggest that for a given optical thickness, the influence of particle shape on the radiative forcing caused by a cloud composed of small ice crystals can be negligible.

This article describes the participatory research process, results, action plan, and implications of the community health information needs assessment conducted within the African American community in two South Carolina counties. The REACH 2010: Charleston and Georgetown Diabetes Coalition library program is a partnership among community organizations, public and health sciences libraries, and lay community health advisors. A planning committee studied digital divide issues related to health information, designed and implemented a survey, held focus groups, analyzed data, identified needs and assets, and formulated an action plan to increase the dissemination of diabetes information. Key survey findings show that older (older than 60) and less educated (fewer than 12 years of education) African Americans in Charleston and Georgetown counties lack skills to access Internet and library services and suffer disparities in health information. Based on assessment evidence, the community plans to increase Internet access points and provide a train-the-trainer program to teach people skills for using Internet and library resources to get high-quality information about diabetes and its complications. This process taps community resources, builds local capacities and technical skills, educates about health, and empowers participants as active partners in their own health and their community’s health.

PURPOSE: This study describes the experiences of workers hired under consumer direction. Design and Methods: Medicaid beneficiaries who volunteered for the Cash and Counseling demonstration were randomly assigned to the treatment group, which could participate in the consumer-directed program, or the control group, which was referred to agency care. Paid workers for both groups were surveyed about 10 months after demonstration enrollment. RESULTS: Directly hired workers for the treatment group were nearly always the consumers' friends or relatives. The two groups received similar wages and both were highly satisfied with their working conditions and the supervision they received. Compared with agency workers, directly hired workers who lived with or were related to the consumer were more likely to report emotional strain and a desire for more respect from the consumer's family; however, no such differences were observed for directly hired workers who were not relatives. Directly hired workers and agency workers providing comparable amounts of care reported similar levels of injury and physical strain, although directly hired workers received less formal training. Implications: The Cash and Counseling model does not appear to cause adverse consequences for the hired workers. Directly hired workers report high levels of job satisfaction and do not suffer physical or emotional hardship beyond what might be expected for individuals providing care to relatives. However, states might be able to reduce emotional strain and injuries by providing educational materials and referrals for consumers, their families, and workers, and by having counselors monitor workers' well-being. Language: en

Consistent and validated data sets of satellite-borne radiances and of a large variety of products describing the characteristics of terrestrial cloud and radiation fields have been produced within the International Satellite Cloud Climatology Project (ISCCP) covering the years 1983 through to 2003. A subset (annual and seasonal averages of the 5 year period 1991 to 1995) is used in this paper to discuss in greater detail the effect of clouds on the radiation fields at the upper and lower boundary of the atmosphere and in particular on the loss and gain (vertical divergence) of radiant energy by the atmosphere itself. Although this subset covers the effects of the Pinatubo eruption (June 1991) and of the strong El Nino event in 1992–93, which indeed caused ‘anomalies in the average aerosol and cloud fields in the tropics and subtropics’. However, our regional averages of the radiation budget at the top of the atmosphere and at ground over a period of 5 years should be within 2–5 W m−2 of longer term averages. We find very interesting spatial patterns in the global distributions of all quantities, which can be explained in part by various cloud field characteristics and by the continental surface characteristics. Most are known from similar studies with radiation budget measurements. Possibly for the first time, we show global fields of the vertical flux divergence of solar and terrestrial radiation within the atmosphere and of the effects of clouds. Both polar regions, various portions of China and the areas of persistent subtropical maritime stratocumulus fields over the Pacific and Atlantic Oceans and of cloud fields associated with the intertropical convergence zone (ITCZ) offer specific features for further analyses. This ISCCP data set seems to underestimate the absorption of solar radiation in the tropical and subtropical atmosphere by about 10 to 20 W m−2. There is a disagreement of about 30 W m−2 in global averages of the gain and loss of solar and terrestrial radiation in the atmosphere between this and two other independent data sets, which needs thorough investigation, since such data are required to validate the radiation budgets within circulation and climate models and for other climate studies. Such an assessment of radiation budget data is now under way within the auspices of the World Climate Research Programme. Copyright © 2005 Royal Meteorological Society

Racial and Ethnic Approaches to Community Health (REACH 2010) is a U.S. Centers for Disease Control and Prevention demonstration program that responds to the U.S. Department of Health and Human Services' goal to eliminate racial and ethnic disparities in health status by the year 2010. As part of REACH 2010, community projects were funded to develop, implement, and evaluate community action plans to improve health care and outcomes for racial and ethnic populations. This article describes the program and details the progress of the REACH 2010: Charleston and Georgetown Diabetes Coalition in reducing disparities in care. Approaches employed by the Coalition included community development, empowerment, and education related to diabetes; health systems change associated with access, care, and education; and coalition advocacy. Racial disparities were identified for 12,000 African Americans with diabetes in this urban/rural South Carolina community. After 24 months, significant differences that initially ranged from 11% to 28% in African Americans (when compared with whites/others) were not observed on 270 chart audits for A1C, lipid and kidney testing, eye examinations, and blood pressure control. Future efforts will focus on maintaining progress, eliminating other disparities, and identifying the contributions of each intervention in eliminating racial disparities.

Statistical scale-by-scale analysis, for the first time, has been applied to the aerosol optical thickness (AOT) retrieved from the Multi-Filter Rotating Shadowband Radiometer (MFRSR) network. The MFRSR data were collected in September 2000 from the dense local network operated by the U.S. Department of Energy Atmospheric Radiation Measurement program, located in Oklahoma and Kansas. These data have 20-s temporal resolution. The instrument sites form an irregular grid with the mean distance between neighboring sites about 80 km. It is found that temporal variability of AOT can be separated into two well-established scale-invariant regimes: 1) microscale (0.5‐15 km), where fluctuations are governed by 3D turbulence, and 2) intermediate scale (15‐100 km), characterized by a transition toward large-scale 2D turbulence. The spatial scaling of AOT was determined by the comparison of retrievals between different instrument sites (distance range 30‐400 km). The authors investigate how simultaneous determination of AOT scaling in space and time can provide means to examine the validity of Taylor’s frozen turbulence hypothesis. The temporal evolution of AOT scaling exponents during the month appeared to be well correlated with changes in aerosol vertical distribution, while their spatial variability reflects the concavity/convexity of the site topography. Explanations based on dynamical processes in atmospheric convective boundary layer are suggested.

The purpose of this project was to determine the accuracy in lipids measurement and risk factor classification using Reflotron, Cholestech, and Ektachem DT-60 dry-chemistry analyzers. Plasma and capillary venous blood from fasting subjects (n = 47) were analyzed for total cholesterol (TC), high density lipoprotein (HDL-C), and triglycerides (TG) using these analyzers and a CDC certified laboratory. Accuracy was evaluated by comparing the results of each portable analyzer against the CDC reference method. One-way ANOVAs were performed for TC, HDL-C, and TG between all portable analyzers and the reference method. Chi-square was used for risk classification (2001 NIH Guidelines). Compared to the reference method, the Ektachem and Reflotron provided significantly lower values for TC (p < .05). In addition, the Cholestech and Ektachem values for HDL-C were higher than the CDC (p < .05). The Reflotron and Cholestech provided higher values of TG than the CDC (p < .05). Chi-squares analyses for risk classification were not significant (p > .45) between analyzers. According to these results, the Ektachem and Cholestech analyzers met the current NCEP III guidelines for accuracy in measurement of TC, while only Ektachem met guidelines for TG. All 3 analyzers provided a good overall risk classification; however, values of HDL-C should be only used for screening purposes.

In this paper, tradeoffs between speed and accuracy for the atmospheric correction of hyperspectral imagery are examined. Among the issues addressed are the use of scattering calculations on a sparse spectral grid and consequent accuracy and speed tradeoffs, methods for minimizing the required number of quadrature points in multiple-scattering calculations, effects of the vertical profiles of aerosols and absorbing gases on atmospheric correction, and efficient approaches for including the effects of sensor variability (or imperfections) on atmospheric correction.

As states seek to improve home and community-based services for people with disabilities, many are incorporating consumer-directed supportive services into their Medicaid programs. The national Cash and Counseling Demonstration uses a randomized design to compare an innovative model of consumer direction with the traditional agency-directed approach. This paper presents findings from the first demonstration program to be implemented, in Arkansas. Our survey of 1,739 elderly and nonelderly adults showed that relative to agency-directed services, Cash and Counseling greatly improved satisfaction and reduced most unmet needs. Moreover, contrary to some concerns, it did not adversely affect participants' health and safety.

The Cash and Counseling Demonstration gives Medicaid beneficiaries who are eligible for personal care services a consumer-directed allowance in lieu of traditional agency services. Using survey and Medicaid claims data on 2,008 adult applicants randomly assigned to treatment or control groups, we find the program increased the receipt of paid care but reduced unpaid care. The treatment group had higher Medicaid personal care expenditures than controls did, because many controls received no paid help, and recipients obtained only two-thirds of entitled services. By the second year after enrollment, these higher personal care expenditures were offset by lower spending for nursing homes and other Medicaid services.

A retrieval algorithm for processing multifilter rotating shadowband radiometer (MFRSR) data from clear and partially cloudy days is described and validated. This method, while complementary to the Langley approach, uses consistency between the direct normal and diffuse horizontal measurements combined with a regression technique to simultaneously retrieve daily time series of column mean aerosol particle size, aerosol optical depth, NO2, and ozone amounts along with the instrument's calibration constants. Comparison with the traditional Langley calibration method demonstrates two advantages of the approach described here: greater calibration stability and a decreased sensitivity of retrievals to calibration errors.