869 resultados para REMOTE DISCHARGE


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Objectives: Depression is associated with poor prognosis in patients with cardiovascular disease (CVD). We hypothesized that depressive symptoms at discharge from a cardiac rehabilitation program are associated with an increased risk of future CVD-related hospitalizations. Methods: We examined 486 CVD patients (mean age = 59.8 ± 11.2) who enrolled in a comprehensive 3-month rehabilitation program and completed the depression subscale of the Hospital Anxiety and Depression Scale (HADS-D). At follow-up we evaluated the predictive value of depressive symptoms for CVD-related hospitalizations, controlling for sociodemographic factors, cardiovascular risk factors, and disease severity. Results: During a mean follow-up of 41.5 ± 15.6 months, 63 patients experienced a CVD-related hospitalization. The percentage of depressive patients (HADS-D ≥ 8) decreased from 16.9% at rehabilitation entry to 10.7% at discharge. Depressive symptoms at discharge from rehabilitation were a significant predictor of outcome (HR 1.32, 95% CI 1.09–1.60; p =0.004). Patients with clinically relevant depressive symptoms at discharge had a 2.5-fold increased relative risk of poor cardiac prognosis compared to patients without clinically relevant depressive symptoms independently of other prognostic variables. Conclusion: In patients with CVD, depressive symptoms at discharge from rehabilitation indicated a poor cardiac prognosis.

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Urban agriculture is a phenomenon that can be observed world-wide, particularly in cities of devel-oping countries. It is contributing significantly to food security and food safety and has sustained livelihood of the urban and peri-urban low income dwellers in developing countries for many years. Population increase due to rural-urban migration and natural, coupled with formal as well as infor-mal urbanization are competing with urban farming for available space and scarce water resources. A multitemporal multisensoral urban change analysis over the period of 25 years (1982-2007) was performed in order to measure and visualize the urban expansion along the Kizinga and Mzinga valley in the South of Dar es Salaam. Airphotos and VHR satellite data were analyzed by using a combination of a composition of anisotropic textural measures and spectral information. The study revealed that unplanned built-up area is expanding continuously and vegetation covers and agricultural lands decline at a fast rate. The validation showed that the overall classification accuracy varied depending on the database. The extracted built-up areas were used for visual in-terpretation mapping purposes and served as information source for another research project. The maps visualize an urban congestion and expansion of nearly 18% of the total analyzed area that had taken place in the Kizinga valley between 1982 and 2007. The same development can be ob-served in the less developed and more remote Mzinga valley between 1981 and 2002. Both areas underwent fast changes where land prices still tend to go up and an influx of people both from rural and urban areas continuously increase density with the consequence of increasing multiple land use interests.

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Facilitation is a major force shaping the structure and diversity of plant communities in terrestrial ecosystems. Detecting positive plant–plant interactions relies on the combination of field experimentation and the demonstration of spatial association between neighboring plants. This has often restricted the study of facilitation to particular sites, limiting the development of systematic assessments of facilitation over regional and global scales. Here we explore whether the frequency of plant spatial associations detected from high-resolution remotely sensed images can be used to infer plant facilitation at the community level in drylands around the globe. We correlated the information from remotely sensed images freely available through Google Earth with detailed field assessments, and used a simple individual-based model to generate patch-size distributions using different assumptions about the type and strength of plant–plant interactions. Most of the patterns found from the remotely sensed images were more right skewed than the patterns from the null model simulating a random distribution. This suggests that the plants in the studied drylands show stronger spatial clustering than expected by chance. We found that positive plant co-occurrence, as measured in the field, was significantly related to the skewness of vegetation patch-size distribution measured using Google Earth images. Our findings suggest that the relative frequency of facilitation may be inferred from spatial pattern signals measured from remotely sensed images, since facilitation often determines positive co-occurrence among neighboring plants. They pave the road for a systematic global assessment of the role of facilitation in terrestrial ecosystems. Read More: http://www.esajournals.org/doi/10.1890/14-2358.1

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A new methodology based on combining active and passive remote sensing and simultaneous and collocated radiosounding data to study the aerosol hygroscopic growth effects on the particle optical and microphysical properties is presented. The identification of hygroscopic growth situations combines the analysis of multispectral aerosol particle backscatter coefficient and particle linear depolarization ratio with thermodynamic profiling of the atmospheric column. We analyzed the hygroscopic growth effects on aerosol properties, namely the aerosol particle backscatter coefficient and the volume concentration profiles, using data gathered at Granada EARLINET station. Two study cases, corresponding to different aerosol loads and different aerosol types, are used for illustrating the potential of this methodology. Values of the aerosol particle backscatter coefficient enhancement factors range from 2.1 ± 0.8 to 3.9 ± 1.5, in the ranges of relative humidity 60–90 and 40–83%, being similar to those previously reported in the literature. Differences in the enhancement factor are directly linked to the composition of the atmospheric aerosol. The largest value of the aerosol particle backscatter coefficient enhancement factor corresponds to the presence of sulphate and marine particles that are more affected by hygroscopic growth. On the contrary, the lowest value of the enhancement factor corresponds to an aerosol mixture containing sulphates and slight traces of mineral dust. The Hänel parameterization is applied to these case studies, obtaining results within the range of values reported in previous studies, with values of the γ exponent of 0.56 ± 0.01 (for anthropogenic particles slightly influenced by mineral dust) and 1.07 ± 0.01 (for the situation dominated by anthropogenic particles), showing the convenience of this remote sensing approach for the study of hygroscopic effects of the atmospheric aerosol under ambient unperturbed conditions. For the first time, the retrieval of the volume concentration profiles for these cases using the Lidar Radiometer Inversion Code (LIRIC) allows us to analyze the aerosol hygroscopic growth effects on aerosol volume concentration, observing a stronger increase of the fine mode volume concentration with increasing relative humidity.

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The evolution of landscapes crucially depends on the climate history. This is particularly evident in South America where landscape responses to orbital climate shifts have been well documented. However, while most studies have focused on inferring temperature variations from paleoclimate proxy data, estimates of water budget changes have been complicated because of a lack of adequate physical information. Here, we present a methodology and related results, which allowed us to extract water discharge values from the sedimentary record of the 40 Ka-old fluvial terrace deposits in the Pisco valley, western Peru. In particular, this valley hosts a Quaternary cut-and-fill succession that we used, in combination with beryllium-10 (10Be)-based sediment flux, gauging records, channel geometries and grain size measurements, to quantitatively assess sediment and water discharge values c. 40 Ka ago in relation to present-day conditions. We compare these discharge estimates to the discharge regime of the modern Pisco River and find that the water discharge of the paleo-Pisco River, during the Minchin pluvial period c. 40 Ka ago, was c. 7–8 times greater than the modern Pisco River if considering the mean and the maximum water discharge. In addition, the calculations show that inferred water discharge estimates are mainly dependent on channel gradients and grain size values, and to a lesser extent on channel width measures. Finally, we found that the c. 40 Ka-old Minchin terrace material was poorer sorted than the modern deposits, which might reflect that sediment transport during the past period was characterized by a larger divergence from equal mobility compared to the modern situation. In summary, the differences in grain size distribution and inferred water discharge estimates between the modern and the paleo-Pisco River suggests that the 40 Ka-old Minchin period was characterized by a wetter climate and more powerful flood events.

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An efficient and reliable automated model that can map physical Soil and Water Conservation (SWC) structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and ArcGIS, ERDAS IMAGINE, and SDC Morphology Toolbox for MATLAB and statistical techniques. The model was developed using the following procedures: (1) a high-pass spatial filter algorithm was applied to detect linear features, (2) morphological processing was used to remove unwanted linear features, (3) the raster format was vectorized, (4) the vectorized linear features were split per hectare (ha) and each line was then classified according to its compass direction, and (5) the sum of all vector lengths per class of direction per ha was calculated. Finally, the direction class with the greatest length was selected from each ha to predict the physical SWC structures. The model was calibrated and validated on the Ethiopian Highlands. The model correctly mapped 80% of the existing structures. The developed model was then tested at different sites with different topography. The results show that the developed model is feasible for automated mapping of physical SWC structures. Therefore, the model is useful for predicting and mapping physical SWC structures areas across diverse areas.

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We present the evolution of oceanographic conditions off the western coast of South America between 1996 and 1999, including the cold periods of 1996 and 1998-1999 and the 1997-1998 El Niño, using satellite observations of sea level, winds, sea surface temperature (SST), and chlorophyll concentration. Following a period of cold SST and low sea levels in 1996, both were anomalously high between March 1997 and May 1998. The anomalies were greatest between 5 degrees S and 15 degrees S, although they extended beyond 40 degrees S. Two distinct peaks in sea level and SST occurred in June-July 1997 and December 1997 to January 1998, separated by a relaxation period (August-November) of weaker anomalies. Satellite winds were upwelling favorable throughout the time period for most of the region and in fact increased between November 1997 and March 1998 between 5 degrees S and 25 degrees S. Satellite-derived chlorophyll concentrations are available for November 1996 to June 1997 (Ocean Color and Temperature Sensor (OCTS)) and then from October 1997 to present (Sea-viewing Wide Field-of-view Sensor (SeaWiFS)). Near-surface chlorophyll concentrations fell from May to June 1997 and from December 1997 to March 1998. The decrease was more pronounced in northern Chile than off the coast of Peru or central Chile and was stronger for larger cross-shelf averaging bins since nearshore concentrations remained relatively high.

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As the requirements for health care hospitalization have become more demanding, so has the discharge planning process become a more important part of the health services system. A thorough understanding of hospital discharge planning can, then, contribute to our understanding of the health services system. This study involved the development of a process model of discharge planning from hospitals. Model building involved the identification of factors used by discharge planners to develop aftercare plans, and the specification of the roles of these factors in the development of the discharge plan. The factors in the model were concatenated in 16 discrete decision sequences, each of which produced an aftercare plan.^ The sample for this study comprised 407 inpatients admitted to the M. D. Anderson Hospital and Tumor Institution at Houston, Texas, who were discharged to any site within Texas during a 15 day period. Allogeneic bone marrow donors were excluded from the sample. The factors considered in the development of discharge plans were recorded by discharge planners and were used to develop the model. Data analysis consisted of sorting the discharge plans using the plan development factors until for some combination and sequence of factors all patients were discharged to a single site. The arrangement of factors that led to that aftercare plan became a decision sequence in the model.^ The model constructs the same discharge plans as those developed by hospital staff for every patient in the study. Tests of the validity of the model should be extended to other patients at the MDAH, to other cancer hospitals, and to other inpatient services. Revisions of the model based on these tests should be of value in the management of discharge planning services and in the design and development of comprehensive community health services.^