880 resultados para Attributes


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A decision-maker, when faced with a limited and fixed budget to collect data in support of a multiple attribute selection decision, must decide how many samples to observe from each alternative and attribute. This allocation decision is of particular importance when the information gained leads to uncertain estimates of the attribute values as with sample data collected from observations such as measurements, experimental evaluations, or simulation runs. For example, when the U.S. Department of Homeland Security must decide upon a radiation detection system to acquire, a number of performance attributes are of interest and must be measured in order to characterize each of the considered systems. We identified and evaluated several approaches to incorporate the uncertainty in the attribute value estimates into a normative model for a multiple attribute selection decision. Assuming an additive multiple attribute value model, we demonstrated the idea of propagating the attribute value uncertainty and describing the decision values for each alternative as probability distributions. These distributions were used to select an alternative. With the goal of maximizing the probability of correct selection we developed and evaluated, under several different sets of assumptions, procedures to allocate the fixed experimental budget across the multiple attributes and alternatives. Through a series of simulation studies, we compared the performance of these allocation procedures to the simple, but common, allocation procedure that distributed the sample budget equally across the alternatives and attributes. We found the allocation procedures that were developed based on the inclusion of decision-maker knowledge, such as knowledge of the decision model, outperformed those that neglected such information. Beginning with general knowledge of the attribute values provided by Bayesian prior distributions, and updating this knowledge with each observed sample, the sequential allocation procedure performed particularly well. These observations demonstrate that managing projects focused on a selection decision so that the decision modeling and the experimental planning are done jointly, rather than in isolation, can improve the overall selection results.

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Tomato ( Lycopersicon esculentum Mill) is the leading vegetable in terms of production in Kenya. The Kenyan local market has a wide variety of tomato cultivars with a wide range of morphological and sensorial characteristics. However, information on the nutritional and postharvest quality of these varieties is lacking. The aim of this research was to investigate and identify tomato varieties of superior postharvest quality and recommend them to small and medium scale farmers. In this study, six tomato varieties were grown in a greenhouse and analyzed at three maturity stages (mature green, turning and red ripe). The tomatoes were analyzed at specific days after harvest and storage at room temperature (25o C). Percentage weight loss, color, respiration and ethylene production rates were analyzed to assess the postharvest quality of the tomatoes. The color was measured using a Minolta Chromameter while the respiration rate and ethylene production rates were determined using the static system approach. Color, weight loss, respiration and ethylene production rates were positively affected by storage time when harvested at the three maturity stages. The percentage weight loss of the tomato fruits was higher in the determinate varieties, and at the turning stage of maturity (3.8 %). Minor color changes were observed after storage of the tomatoes harvested at red stage for six days. Both rates of respiration and ethylene production were low, with the respiration rate ranging between 56-10 ml CO2 Kg-1h-1. The Chonto F1 variety had the highest rate of ethylene production (5.4 μL C2H4 Kg-1h-1) on the 4th day of storage after harvest at the red ripe stage. Overall, the indeterminate tomato varieties displayed better postharvest quality that can prolong the fruits shelf life for marketing. In turn, the turning stage of maturity proved to be a better stage to harvest tomatoes as the color development was more uniform.

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This study evaluated the antifungal susceptibility profile and the production of potential virulence attributes in a clinical strain of Candida nivariensis for the first time in Brazil, as identified by sequencing the internal transcribed spacer (ITS)1-5.8S-ITS2 region and D1/D2 domains of the 28S of the rDNA. For comparative purposes, tests were also performed with reference strains. All strains presented low planktonic minimal inhibitory concentrations (PMICs) to amphotericin B (AMB), caspofungin (CAS), and voriconazole. However, our strain showed elevated planktonic MICs to posaconazole (POS) and itraconazole, in addition to fluconazole resistance. Adherence to inert surfaces was conducted onto glass and polystyrene. The biofilm formation and antifungal susceptibility on biofilmgrowing cells were evaluated by crystal violet staining and a XTT reduction assay. All fungal strains were able to bind both tested surfaces and form biofilm, with a binding preference to polystyrene (p < 0.001). AMB promoted significant reductions (≈50%) in biofilm production by our C. nivariensis strain using both methodologies. This reduction was also observed for CAS and POS, but only in the XTT assay. All strains were excellent protease producers and moderate phytase producers, but lipases were not detected. This study reinforces the pathogenic potential of C. nivariensis and its possible resistance profile to the azolic drugs generally used for candidiasis management.

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Banana is one of the most consumed fruits in the world, which is grown in most tropical countries. The objective of this work was to evaluate the main attributes of soil fertility in a banana crop under two cover crops and two root development locations. The work was conducted in Curaçá, BA, Brazil, between October 2011 and May 2013, using a randomized block design in split plot with five repetitions. Two cover crops were assessed in the plots, the cover 1 consisting of Pueraria phaseoloid es, and the cover 2 consisting of a crop mix with Sorghum bicolor, Ricinus commun is L., Canavalia ensiform is, Mucuna aterrima and Zea mays, and two soil sampling locations in the subplots, between plants in the banana rows (location 1) and between the banana rows (location 2). There were significant and independent effects for the cover crop and sampling location factors for the variables organic matter, Ca and P, and significant effects for the interaction between cover crops and sampling locations for the variables potassium, magnesium and total exchangeable bases. The cover crop mix and the between-row location presented the highest organic matter content. Potassium was the nutrient with the highest negative variation from the initial content and its leaf content was below the reference value, however not reducing the crop yield. The banana crop associated with crop cover using the crop mix provided greater availability of nutrients in the soil compared to the coverage with tropical kudzu.

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Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

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Purpose The purpose of the research work is to investigate the importance of the communication in the cross-functional teams and in what which communicational tools provide better convenience of communication in cross-functional team members. Methodology An empirical study including the data collection from the interviews conducted from the participants working in cross-functional teams. Qualitative approach has been adopted to understand the communicational attributes in the cross-functional teams. For the analysis both deductive and abductive approach has been used. With the help of theoretical framework and empirical data, conclusions drown for better understanding of the concept. Findings The author has divided the search in two main segments, communicational effects on cross-functional team performance and effectiveness of particular communicational tools used by team members and team leaders. Empirical findings shows that without proper communication, cross-functional team are less tend to perform well to achieve set goals as well as face to face communications are more effective than other communicational tools.  Research limitations The research work is limited to Scandinavian countries. Organizational communicational structures are not studied due to time factor. Other limitation of this research work is effect of cultural differences on communication. Implications The research work provides deep understanding of the different communicational effects on cross-functional team performance. The choice of communicational tool and proportional importance for the team members will help managers while selecting the tools of communication with the team members. Originality / value During the literature studies, author determined that there is potential of research for the communicational tools used in cross-functional team communications. The social media is taking over the traditional communicational tools which provide value for findings. 

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Using a top-down modelling approach, a balanced trophic food web model of a water reservoir of the Ria Formosa lagoonal system was constructed. Few adjustments of input data were necessary to run the model since most of the parameters were estimated at the study site and the characteristics of the water reservoir allowed a high degree of control and precision in terms of sampling and data collection. Trophic levels of the 14 compartments included in the model varied between 1.0 for primary producers and detritus to 3.4 for carnivorous fish and the 14 groups were aggregated in a food chain with six trophic levels. The water reservoir has a detritus based food chain, with the majority of the biomass concentrated in the first two levels, the producers level and the herbivore/detritivore level (97.6%). The transfer efficiencies were low, and decreased with increasing level number, varying between 6.0 and 0.2%. The degree of "ecosystem maturity" was difficult to establish, but several parameters indicate that it could be high. The water reservoir studied, which has similar environmental and ecological characteristics as the Ria Formosa lagoon. is near its carrying capacity. (C) 2004, Elsevier B.V. All rights reserved.

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Coffea sp. is cultivated in large areas, using both conventional and organic management. However, information about the sustainability of these two management systems is still deficient. The objective of the present study was to evaluate the physical properties of soil cultivated with Conilon coffee (C. canephora) under organic and conventional management. Two areas cultivated with Conilon coffee (under organic and conventional management) and a fragment of Atlantic forest, used as a reference, were selected for the experiment. Soil granulometry, hydraulic conductivity, water retention curve, resistance to penetration, porosity, optimal hydric interval, and other physical characteristics were measured at depths of 0 to 10 and 10 to 20 cm. The data was submitted to multivariate and descriptive statistical analyses. Higher similarity was observed between the soil cultivated with Conilon coffee under organic management and the Atlantic forest soil. Soil resistance to penetration at 10, 30, 100, 500 and 1500 kPa, macro porosity, density and total porosity were the main physical properties that differentiated both management systems studied. The non-use of agricultural machinery and the addition of organic matter may be the main reasons for higher soil sustainability observed under organic management when compared with the conventional system.

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The soil carbon under Amazonian forests has an important roles in global changing, making information on the soil content and depths of these stocks are considerable interest in efforts to quantify soil carbon emissions to the atmosphere.This study quantified the content and soil organic carbon stock under primary forest up to 2 m depth, at different topographic positions, at Cuieiras Biological Reserve, Manaus/ ZF2, km 34, in the Central Amazon, evaluating the soil attributes that may influence the permanence of soil carbon. Soil samples were collected along a transect of 850 m on topographic gradient Oxisol (plateau), Ultisol (slope) and Spodosol (valley). The stocks of soil carbon were obtained by multiplying the carbon content, soil bulk density and trickiness of soil layers. The watershed was delimited by using STRM and IKONOS images and the carbon contend obtained in the transects was extrapolated as a way to evaluate the potential for carbon stocks in an area of 2678.68 ha. The total SOC was greater in Oxisol followed by Spodosol and Ultisol. It was found direct correlations between the SOC and soil physical attributes. Among the clay soils (Oxisol and Ultisol), the largest stocks of carbon were observed in Oxisol at both the transect (90 to 175.5 Mg C ha-1) as the level of watershed (100.2 to 195.2 Mg C ha-1). The carbon stocks under sandy soil (Spodosol) was greater to clay soils along the transect (160-241 Mg C ha-1) and near them in the Watershed (96.90 to 146.01 Mg C ha-1).

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The aim of this study was to determine the effect of pearl millet intercropped with other cover crops on mineral forms of N and urease activity in soil, nitrate reductase activity in the leaves of the follow-up rice crop, as well as the yield components of this rice crop. The experiment was performed in the year 2012/2013 at two locations of the Brazilian Cerrado.

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Two distinct maintenance-data-models are studied: a government Enterprise Resource Planning (ERP) maintenance-data-model, and the Software Engineering Industries (SEI) maintenance-data-model. The objective is to: (i) determine whether the SEI maintenance-data-model is sufficient in the context of ERP (by comparing with an ERP case), (ii) identify whether the ERP maintenance-data-model in this study has adequately captured the essential and common maintenance attributes (by comparing with the SEI), and (iii) proposed a new ERP maintenance-data-model as necessary. Our findings suggest that: (i) there are variations to the SEI model in an ERP-context, and (ii) there are rooms for improvements in our ERP case’s maintenance-data-model. Thus, a new ERP maintenance-data-model capturing the fundamental ERP maintenance attributes is proposed. This model is imperative for: (i) enhancing the reporting and visibility of maintenance activities, (ii) monitoring of the maintenance problems, resolutions and performance, and (iii) helping maintenance manager to better manage maintenance activities and make well-informed maintenance decisions.