In the past few years sequential data assimilation (SDA) methods have emerged as the best possible method at hand to properly treat all sources of error in hydrological modeling. However, very few studies have actually implemented SDA methods using realistic input error models for precipitation. In this study we use particle filtering as a SDA method to propagate input errors through a conceptual hydrologic model and quantify the state, parameter and streamflow uncertainties. Recent progress in satellite-based precipitation observation techniques offers an attractive option for considering spatiotemporal variation of precipitation. Therefore, we use the PERSIANN-CCS precipitation product to propagate input errors through our hydrologic model. Some uncertainty scenarios are set up to incorporate and investigate the impact of the individual uncertainty sources from precipitation, parameters and also combined error sources on the hydrologic response. Also probabilistic measure are used to quantify the quality of ensemble prediction. Copyright 2006 by the American Geophysical Union.

Despite many interventions to promote medication adherence in older adults, we know little about how medication adherence has improved as a result of such interventions. The purpose of this study was to examine the long-term program impacts on medication adherence from participating in the Chronic Disease Self-Management Program (CDSMP). Secondary data used for this study included the CDSMP participants' sociodemographic characteristics and their baseline and 6- and 12-month follow-up assessments on health-related indicators, including medication adherence, self-rated health, depression, and patient communication skills. This study included those who were 65 years or older, had one or more chronic conditions, and attended at least the first or second session. Linear mixed models were used to analyze the impacts of short-term (6 months) changes in health-related indicators on long-term (12 months) changes in medication nonadherence. The subset analyses were performed among participants with self-rated major depression at baseline. This study included 687 participants. Self-reported medication adherence did not improve significantly at 6-month follow-up assessment but significantly improved at 12-month follow-up assessment. Among those with self-reported major depression at baseline assessment, the short-term improvements in depression and self-rated health were associated with long-term changes in medication adherence. The long-term impacts of the CDSMP on medication adherence were influenced by the short-term program impacts on health-related indicators. More targeted interventions are needed for patients with major depression, and programs such as the CDSMP can be particularly helpful among the population.

Introduction

Cost-related medication nonadherence (CRN) can negatively affect chronic disease prevention and management in an aging population. Limited data are available on the interacting influences among such factors as availability of financial resources, attitudes and beliefs of patients, and CRN. The objective of this study was to examine the causal paths among financial resource availability, patient attitudes and beliefs, and CRN.

Methods

We used a nationally representative sample (n = 4,818) from the 2015 National Health Interview Survey; selected respondents were aged 65 or older, had a diagnosis of hypertension or diabetes or both, and were prescribed medication for at least 1 of these conditions. We performed structural equation modeling to examine whether perceived medication affordability, access to health care, and patient satisfaction influenced the effects of financial resource availability on CRN (skipped doses, took less medicine, or delayed filling a prescription to save money).

Results

Six percent of respondents reported CRN in the previous 12 months. The model showed a good to fair fit, and all paths were significant (P < .05) except for age. The effects of financial resource availability on CRN was mediated through perceived medication affordability, access to health care, and patient satisfaction with health care services.

Conclusion

This study suggests that patients' attitudes and beliefs can mediate the effects of financial resource availability on CRN. We call for senior-friendly public health interventions that can address these modifiable barriers to reduce CRN among older adults with chronic conditions.

Recent progress in satellite remote-sensing techniques for precipitation estimation, along with more accurate tropical rainfall measurements from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and precipitation radar (PR) instruments, have made it possible to monitor tropical rainfall diurnal patterns and their intensities from satellite information. One year (August 1998-July 1999) of tropical rainfall estimates from the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) systems were used to produce monthly means of rainfall diurnal cycles at hourly and 1° × 1° scales over a domain (30°S-30°N, 80°E-10°W) from the Americas across the Pacific Ocean to Australia and eastern Asia. The results demonstrate pronounced diurnal variability of tropical rainfall intensity at synoptic and regional scales. Seasonal signals of diurnal rainfall are presented over the large domain of the tropical Pacific Ocean, especially over the ITCZ and South Pacific convergence zone (SPCZ) and neighboring continents. The regional patterns of tropical rainfall diurnal cycles are specified in the Amazon, Mexico, the Caribbean Sea, Calcutta, Bay of Bengal, Malaysia, and northern Australia. Limited validations for the results include comparisons of 1) the PERSIANN-derived diurnal cycle of rainfall at Rondonia, Brazil, with that derived from the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE) radar data; 2) the PERSIANN diurnal cycle of rainfall over the western Pacific Ocean with that derived from the data of the optical rain gauges mounted on the TOGA-moored buoys: and 3) the monthly accumulations of rainfall samples from the orbital TMI and PR surface rainfall with the accumulations of concurrent PERSIANN estimates. These comparisons indicate that the PERSIANN-derived diurnal patterns at the selected resolutions produce estimates that are similar in magnitude and phase.

This paper outlines the development of a multi-satellite precipitation estimation methodology that draws on techniques from machine learning and morphology to produce high-resolution, short-duration rainfall estimates in an automated fashion. First, cloud systems are identified from geostationary infrared imagery using morphology based watershed segmentation algorithm. Second, a novel pattern recognition technique, growing hierarchical self-organizing map (GHSOM), is used to classify clouds into a number of clusters with hierarchical architecture. Finally, each cloud cluster is associated with co-registered passive microwave rainfall observations through a cumulative histogram matching approach. The network was initially trained using remotely sensed geostationary infrared satellite imagery and hourly ground-radar data in lieu of a dense constellation of polar-orbiting spacecraft such as the proposed global precipitation measurement (GPM) mission. Ground-radar and gauge rainfall measurements were used to evaluate this technique for both warm (June 2004) and cold seasons (December 2004-February 2005) at various temporal (daily and monthly) and spatial (0.04 and 0.25) scales. Significant improvements of estimation accuracy are found classifying the clouds into hierarchical sub-layers rather than a single layer. Furthermore, 2-year (2003-2004) satellite rainfall estimates generated by the current algorithm were compared with gauge-corrected Stage IV radar rainfall at various time scales over continental United States. This study demonstrates the usefulness of the watershed segmentation and the GHSOM in satellite-based rainfall estimations.

BACKGROUND: Racial/ethnic minority and immigrant caregivers of persons with dementia experience high rates of psychosocial stress and adverse health outcomes. Few culturally tailored mobile health (mHealth) programs were designed for these vulnerable populations. OBJECTIVE: This study reports the development of a culturally tailored mHealth program called Wellness Enhancement for Caregivers (WECARE) to improve caregiving skills, reduce distress, and improve the psychosocial well-being of Chinese American family caregivers of persons with dementia. METHODS: Community-based user-centered design principles were applied in the program development. First, the structure and curriculum of the WECARE program were crafted based on existing evidence-based interventions for caregivers with input from 4 experts. Second, through working closely with 8 stakeholders, we culturally adapted evidence-based programs into multimedia program components. Lastly, 5 target users tested the initial WECARE program; their experience and feedback were used to further refine the program. RESULTS: The resulting WECARE is a 7-week mHealth program delivered via WeChat, a social media app highly popular in Chinese Americans. By subscribing to the official WECARE account, users can receive 6 interactive multimedia articles pushed to their WeChat accounts each week for 7 weeks. The 7 major themes include (1) facts of dementia and caregiving; (2) the enhancement of caregiving skills; (3) effective communication with health care providers, care partners, and family members; (4) problem-solving skills for caregiving stress management; (5) stress reduction and depression prevention; (6) the practice of self-care and health behaviors; and (7) social support and available resources. Users also have the option of joining group chats for peer support. The WECARE program also includes a back-end database that manages intervention delivery and tracks user engagement. CONCLUSIONS: The WECARE program represents one of the first culturally tailored social media-based interventions for Chinese American caregivers of persons with dementia. It demonstrates the use of community-based user-centered design principles in developing an mHealth intervention program in underserved communities. We call for more cultural adaptation and development of mHealth interventions for immigrant and racial/ethnic minority caregivers of persons with dementia.

Rapid urbanization and economic development in East Asia in past decades has led to photochemical air pollution problems such as excess photochemical ozone and aerosol formation. Asian megacities such as Seoul, Tokyo, Shanghai, Guangzhou, and Beijing are surrounded by densely forested areas, and recent research has consistently demonstrated the importance of biogenic volatile organic compounds (VOCs) from vegetation in determining oxidation capacity in the suburban Asian megacity regions. Uncertainties in constraining tropospheric oxidation capacity, dominated by hydroxyl radical, undermine our ability to assess regional photochemical air pollution problems. We present an observational data set of CO, NOx, SO2, ozone, HONO, and VOCs (anthropogenic and biogenic) from Taehwa research forest (TRF) near the Seoul metropolitan area in early June 2012. The data show that TRF is influenced both by aged pollution and fresh biogenic volatile organic compound emissions. With the data set, we diagnose HOx (OH, HO2, and RO2) distributions calculated using the University of Washington chemical box model (UWCM v2.1) with near-explicit VOC oxidation mechanisms from MCM v3.2 (Master Chemical Mechanism). Uncertainty from unconstrained HONO sources and radical recycling processes highlighted in recent studies is examined using multiple model simulations with different model constraints. The results suggest that (1) different model simulation scenarios cause systematic differences in HOx distributions, especially OH levels (up to 2.5 times), and (2) radical destruction (HO2 + HO2 or HO2 + RO2) could be more efficient than radical recycling (RO2 + NO), especially in the afternoon. Implications of the uncertainties in radical chemistry are discussed with respect to ozone-VOC-NOx sensitivity and VOC oxidation product formation rates. Overall, the NOx limited regime is assessed except for the morning hours (8 a.m. to 12 p.m. local standard time), but the degree of sensitivity can significantly vary depending on the model scenarios. The model results also suggest that RO2 levels are positively correlated with oxygenated VOCs (OVOCs) production that is not routinely constrained by observations. These unconstrained OVOCs can cause higher-than-expected OH loss rates (missing OH reactivity) and secondary organic aerosol formation. The series of modeling experiments constrained by observations strongly urge observational constraint of the radical pool to enable precise understanding of regional photochemical pollution problems in the East Asian megacity region.

BACKGROUND: Chinese American family caregivers of persons with dementia experience high rates of psychosocial distress and adverse health outcomes. Due to their immigrant and minority status, they face substantial obstacles to care and support, including stigma and misperception of dementia, limited knowledge and use of welfare and services, and poor social support. Few interventions have been developed or tested for this vulnerable population. OBJECTIVE: This study aims to pilot-test the Wellness Enhancement for Caregivers (WECARE) intervention, a culturally tailored program delivered via WeChat, a social media app highly popular in the Chinese population. The 7-week WECARE was designed specifically for Chinese American dementia caregivers to improve their caregiving skills, reduce stress, and enhance psychosocial well-being. Feasibility, acceptability, and preliminary efficacy of the WECARE were assessed in this pilot. METHODS: A total of 24 Chinese American family caregivers of persons with dementia were recruited for a pre-post 1-arm trial of the WECARE. By subscribing to the WECARE official account, participants received interactive multimedia programs on their WeChat account multiple times a week for 7 weeks. A backend database automatically delivered program components and tracked user activities. Three online group meetings were organized to facilitate social networking. Participants completed a baseline and a follow-up survey. Feasibility was assessed by the follow-up rate and curriculum completion rate; acceptability was assessed by user satisfaction and perceived usefulness of the program; and efficacy was assessed with pre-post differences in 2 primary outcomes of depressive symptoms and caregiving burden. RESULTS: The intervention was completed by 23 participants with a retention rate of 96%. Most of them (n=20, 83%) were older than 50 years and the majority (n=17, 71%) were female. The backend database revealed that the mean curriculum completion rate was 67%. Participants also reported high rates of user satisfaction and perceived usefulness of the intervention and high ratings of weekly programs. The intervention led to significant improvement in participants psychosocial health outcomes; their depressive symptoms reduced from 5.74 to 3.35 with an effect size of -0.89 and caregiving burden decreased from 25.78 to 21.96 with an effect size of -0.48. CONCLUSIONS: This pilot study suggests that WeChat-based WECARE intervention was feasible and acceptable; it also demonstrated initial efficacy in improving psychosocial well-being in Chinese American dementia caregivers. Further research with a control group is needed to assess its efficacy and effectiveness. The study highlights the need for more culturally appropriate mobile health interventions for Chinese American family caregivers of persons with dementia.

Epithelial ovarian cancer (EOC) has poor prognosis and rapid recurrence because of widespread dissemination of peritoneal metastases at diagnosis. Multiple pathways contribute to the aggressiveness of ovarian cancer, including hypoxic signaling mechanisms. In this study, we have determined that the hypoxia-inducible histone demethylase KDM4B is expressed in ∼60% of EOC tumors assayed, including primary and matched metastatic tumors. Expression of KDM4B in tumors is positively correlated with expression of the tumor hypoxia marker CA-IX, and is robustly induced in EOC cell lines exposed to hypoxia. KDM4B regulates expression of metastatic genes and pathways, and loss of KDM4B increases H3K9 trimethylation at the promoters of target genes like LOXL2, LCN2 and PDGFB. Suppressing KDM4B inhibits ovarian cancer cell invasion, migration and spheroid formation in vitro. KDM4B also regulates seeding and growth of peritoneal tumors in vivo, where its expression corresponds to hypoxic regions. This is the first demonstration that a Jumonji-domain histone demethylase regulates cellular processes required for peritoneal dissemination of cancer cells, one of the predominant factors affecting prognosis of EOC. The pathways regulated by KDM4B may present novel opportunities to develop combinatorial therapies to improve existing therapies for EOC patients.