San Diego State University

About: San Diego State University is a education organization based out in San Diego, California, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 12418 authors who have published 27950 publications receiving 1192375 citations. The organization is also known as: SDSU & San Diego State College.

On the use of MODIS EVI to assess gross primary productivity of North American ecosystems

Abstract: [1] Carbon flux models based on light use efficiency (LUE), such as the MOD17 algorithm, have proved difficult to parameterize because of uncertainties in the LUE term, which is usually estimated from meteorological variables available only at large spatial scales. In search of simpler models based entirely on remote-sensing data, we examined direct relationships between the enhanced vegetation index (EVI) and gross primary productivity (GPP) measured at nine eddy covariance flux tower sites across North America. When data from the winter period of inactive photosynthesis were excluded, the overall relationship between EVI and tower GPP was better than that between MOD17 GPP and tower GPP. However, the EVI/GPP relationships vary between sites. Correlations between EVI and GPP were generally greater for deciduous than for evergreen sites. However, this correlation declined substantially only for sites with the smallest seasonal variation in EVI, suggesting that this relationship can be used for all but the most evergreen sites. Within sites dominated by either evergreen or deciduous species, seasonal variation in EVI was best explained by the severity of summer drought. Our results demonstrate that EVI alone can provide estimates of GPP that are as good as, if not better than, current versions of the MOD17 algorithm for many sites during the active period of photosynthesis. Preliminary data suggest that inclusion of other remote-sensing products in addition to EVI, such as the MODIS land surface temperature (LST), may result in more robust models of carbon balance based entirely on remote-sensing data.

Burnout, self- and supervisor-rated job performance, and absenteeism among nurses.

Abstract: This study examined how job stress and work support predict the experience of burnout and how burnout is related to absenteeism and job performance in a sample of 73 registered nurses. The current study expanded on previous findings by including supervisor ratings of performance and employee records of absenteeism in addition to self-report measures. It also examined the extent to which burnout may mediate the relationships of job stress and social support with these performance indicators. Analyses indicated that levels of work support and job stress were both significant predictors of burnout. Additionally, higher burnout levels were significantly associated with poorer self-rated and supervisor-rated job performance, more sick leave, and more reported absences for mental health reasons. Finally, further analyses suggest that level of burnout served as a mediator of the relationships between social support and self-rated job performance, absences for mental health reasons, and intentions to quit. The findings suggest that burnout not only may negatively impact healthcare providers, but also may influence objective absenteeism and supervisor perceptions of employee performance.

Sleep disturbances in fibromyalgia syndrome: Relationship to pain and depression

Abstract: Objective This study is an examination of sleep, pain, depression, and physical functioning at baseline and 1-year followup among patients with fibromyalgia syndrome (FMS). Although it is clear that these symptoms are prevalent among FMS patients and that they are related, the direction of the relationship is unclear. We sought to identify and report sleep problems in this population and to examine their relationship to pain, depression, and physical functioning. Methods Patients diagnosed with fibromyalgia were recruited from a Southern California health maintenance organization and evaluated according to American College of Rheumatology criteria in the research laboratory. Six hundred patients completed the baseline assessment and 492 completed the 1-year assessment. Measures included the Center for Epidemiologic Studies Depression Scale, the McGill Pain Questionnaire, the Pittsburgh Sleep Quality Index, and the Fibromyalgia Impact Questionnaire. Results The majority of the sample (96% at baseline and 94.7% at 1 year) scored within the range of problem sleepers. Path analyses examined the impact of baseline values on 1-year values for each of the 4 variables. No variable of interest predicted sleep, sleep predicted pain (β = 0.13), pain predicted physical functioning (β = −0.13), and physical functioning predicted depression (β = −0.10). Conclusion These findings highlight the high prevalence of sleep problems in this population and suggest that they play a critical role in exacerbating FMS symptoms. Furthermore, they support limited existing findings that sleep predicts subsequent pain in this population, but also extend the literature, suggesting that sleep may be related to depression through pain and physical functioning.

Masses, radii, and orbits of small kepler planets: the transition from gaseous to rocky planets

Abstract: National Aeronautics and Space Administration (Kepler Participating Scientist Program NNX12AC76G)