433 resultados para 1348
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Menu analysis is the gathering and processing of key pieces of information to make it more manageable and understandable. Ultimately, menu analysis allows managers to make more informed decisions about prices, costs, and items to be included on a menu. The author discusses If labor as well as food casts need to be included in menu analysis and if managers need to categorize menu items differently when doing menu analysis based on customer eating patterns.
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Tide propagation through coastal wetlands is a complex phenomenon affected by vegetation, channels, and tidal conditions. Generally, tidal flow is studied using stage (water level) observations, which provide good temporal resolution, but they are acquired in limited locations. Here, a remote-sensing technique, wetland InSAR (interferometric synthetic aperture radar), is used to detect tidal flow in vegetated coastal environments over broad spatial scales. The technique is applied to data sets acquired by three radar satellites over the western Everglades in south Florida. Interferometric analysis of the data shows that the greatest water-level changes occur along tidal channels, reflecting a high velocity gradient between fast horizontal flow in the channel and the slow flow propagation through the vegetation. The high-resolution observations indicate that the tidal flushing zone extends 2–3 km on both sides of tidal channels and can extend 3–4 km inland from the end of the channel. The InSAR observations can also serve as quantitative constraints for detailed coastal wetland flow models.
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Bottoms—Gay men who prefer to be penetrated, sexually—are more stigmatized than other gay men, and may develop and experience identities differently than other gay, bisexual, or heterosexual men. This paper explores intrinsic dispositions and extrinsic motivations that may lead bottoms to perform and embody psychosocial and sexual identities in intimate, interpersonal, and social contexts.
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Vol. 22, Issue 18, 8 pages
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The purpose of this research was to investigate the influence of elevation and other terrain characteristics over the spatial and temporal distribution of rainfall. A comparative analysis was conducted between several methods of spatial interpolations using mean monthly precipitation values in order to select the best. Following those previous results it was possible to fit an Artificial Neural Network model for interpolation of monthly precipitation values for a period of 20 years, with input values such as longitude, latitude, elevation, four geomorphologic characteristics and anchored by seven weather stations, it reached a high correlation coefficient (r=0.85). This research demonstrated a strong influence of elevation and other geomorphologic variables over the spatial distribution of precipitation and the agreement that there are nonlinear relationships. This model will be used to fill gaps in time-series of monthly precipitation, and to generate maps of spatial distribution of monthly precipitation at a resolution of 1km2.
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Approaches to quantify the organic carbon accumulation on a global scale generally do not consider the small-scale variability of sedimentary and oceanographic boundary conditions along continental margins. In this study, we present a new approach to regionalize the total organic carbon (TOC) content in surface sediments (<5 cm sediment depth). It is based on a compilation of more than 5500 single measurements from various sources. Global TOC distribution was determined by the application of a combined qualitative and quantitative-geostatistical method. Overall, 33 benthic TOC-based provinces were defined and used to process the global distribution pattern of the TOC content in surface sediments in a 1°x1° grid resolution. Regional dependencies of data points within each single province are expressed by modeled semi-variograms. Measured and estimated TOC values show good correlation, emphasizing the reasonable applicability of the method. The accumulation of organic carbon in marine surface sediments is a key parameter in the control of mineralization processes and the material exchange between the sediment and the ocean water. Our approach will help to improve global budgets of nutrient and carbon cycles.
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Bayesian adaptive methods have been extensively used in psychophysics to estimate the point at which performance on a task attains arbitrary percentage levels, although the statistical properties of these estimators have never been assessed. We used simulation techniques to determine the small-sample properties of Bayesian estimators of arbitrary performance points, specifically addressing the issues of bias and precision as a function of the target percentage level. The study covered three major types of psychophysical task (yes-no detection, 2AFC discrimination and 2AFC detection) and explored the entire range of target performance levels allowed for by each task. Other factors included in the study were the form and parameters of the actual psychometric function Psi, the form and parameters of the model function M assumed in the Bayesian method, and the location of Psi within the parameter space. Our results indicate that Bayesian adaptive methods render unbiased estimators of any arbitrary point on psi only when M=Psi, and otherwise they yield bias whose magnitude can be considerable as the target level moves away from the midpoint of the range of Psi. The standard error of the estimator also increases as the target level approaches extreme values whether or not M=Psi. Contrary to widespread belief, neither the performance level at which bias is null nor that at which standard error is minimal can be predicted by the sweat factor. A closed-form expression nevertheless gives a reasonable fit to data describing the dependence of standard error on number of trials and target level, which allows determination of the number of trials that must be administered to obtain estimates with prescribed precision.
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El presente trabajo tiene por objeto estudiar la aplicación de la Real Cédula de 13 de noviembre de 1766, sobre separación de corregimientos e intendencias, en el caso concreto del Ayuntamiento de Granada, durante un período de especial complejidad, el de la Guerra de la Independencia.
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Objective: To examine the effectiveness of an “Enhancing Positive Emotions Procedure” (EPEP) based on positive psychology and cognitive behavioral therapy in relieving distress at the time of adjuvant chemotherapy treatment in colorectal cancer patients (CRC). It is expected that EPEP will increase quality of life and positive affect in CRC patients during chemotherapy treatment intervention and at 1 month follow-up.Method: A group of 24 CRC patients received the EPEP procedure (intervention group), whereas another group of 20 CRC patients did not receive the EPEP (control group). Quality of life (EORTC-QLQC30), and mood (PANAS) were assessed in three moments: prior to enter the study (T1), at the end of the time required to apply the EPEP (T2, 6 weeks after T1), and, at follow-up (T3, one-month after T2). Patient’s assessments of the EPEP (improving in mood states, and significance of the attention received) were assessed with Lickert scales.Results: Insomnia was reduced in the intervention group. Treatment group had better scores on positive affect although there were no significantly differences between groups and over time. There was a trend to better scores at T2 and T3 for the intervention group on global health status, physical, role, and social functioning scales. Patients stated that positive mood was enhanced and that EPEP was an important resource.Conclusions: CRC patients receiving EPEP during chemotherapy believed that this intervention was important. Furthermore, EPEP seems to improve positive affect and quality of life. EPEP has potential benefits, and its implementation to CRC patients should be considered.