909 resultados para dependency of attributes


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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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This chapter uses a qualitative approach to explore the characteristics of newly-bred Chinese entrepreneurs among 14 technology-based companies in Mainland China, Taiwan, and Hong Kong. Internal and external perspectives on studying entrepreneurship were adapted to examine personality attributes and the impacts of social settings on shaping the characteristics of modern Chinese entrepreneurs. The findings show that Chinese entrepreneurs were strongly influenced by the Confucianism, in which learning was upheld as a key to develop internal innovative capabilities for sustaining enterprise growth in the dynamic environment. Chinese entrepreneurs leading technologically innovative companies were also found to be visionary, but with less risk taking; they had exceptional networking capability and political dexterity to build strong relationships with government, industry and community. The tie between the Confucian entrepreneurial attributes and strong government support appears to enable the 'innovation in Chinese way'. Implications of these results are discussed.

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Cardiac autonomic neuropathy (CAN) poses an important clinical problem, which often remains undetected due difficulty of conducting the current tests and their lack of sensitivity. CAN has been associated with growth in the risk of unexpected death in cardiac patients with diabetes mellitus. Heart rate variability (HRV) attributes have been actively investigated, since they are important for diagnostics in diabetes, Parkinson's disease, cardiac and renal disease. Due to the adverse effects of CAN it is important to obtain a robust and highly accurate diagnostic tool for identification of early CAN, when treatment has the best outcome. Use of HRV attributes to enhance the effectiveness of diagnosis of CAN progression may provide such a tool. In the present paper we propose a new machine learning algorithm, the Multi-Layer Attribute Selection and Classification (MLASC), for the diagnosis of CAN progression based on HRV attributes. It incorporates our new automated attribute selection procedure, Double Wrapper Subset Evaluator with Particle Swarm Optimization (DWSE-PSO). We present the results of experiments, which compare MLASC with other simpler versions and counterpart methods. The experiments used our large and well-known diabetes complications database. The results of experiments demonstrate that MLASC has significantly outperformed other simpler techniques.

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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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The application of 3D grain-based modelling techniques is investigated in both small and large scale 3DEC models, in order to simulate brittle fracture processes in low-porosity crystalline rock. Mesh dependency in 3D grain-based models (GBMs) is examined through a number of cases to compare Voronoi and tetrahedral grain assemblages. Various methods are used in the generation of tessellations, each with a number of issues and advantages. A number of comparative UCS test simulations capture the distinct failure mechanisms, strength profiles, and progressive damage development using various Voronoi and tetrahedral GBMs. Relative calibration requirements are outlined to generate similar macro-strength and damage profiles for all the models. The results confirmed a number of inherent model behaviors that arise due to mesh dependency. In Voronoi models, inherent tensile failure mechanisms are produced by internal wedging and rotation of Voronoi grains. This results in a combined dependence on frictional and cohesive strength. In tetrahedral models, increased kinematic freedom of grains and an abundance of straight, connected failure pathways causes a preference for shear failure. This results in an inability to develop significant normal stresses causing cohesional strength dependence. In general, Voronoi models require high relative contact tensile strength values, with lower contact stiffness and contact cohesional strength compared to tetrahedral tessellations. Upscaling of 3D GBMs is investigated for both Voronoi and tetrahedral tessellations using a case study from the AECL’s Mine-by-Experiment at the Underground Research Laboratory. An upscaled tetrahedral model was able to reasonably simulate damage development in the roof forming a notch geometry by adjusting the cohesive strength. An upscaled Voronoi model underestimated the damage development in the roof and floor, and overestimated the damage in the side-walls. This was attributed to the discretization resolution limitations.

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INTRODUCTION: Prevalence of walking and cycling for transport is low and varies greatly across countries. Few studies have examined neighborhood perceptions related to walking and cycling for transport in different countries. Therefore, it is challenging to prioritize appropriate built-environment interventions. OBJECTIVES: The aim of this study was to examine the strength and shape of the relationship between adults' neighborhood perceptions and walking and cycling for transport across diverse environments. METHODS: As part of the International Physical activity and Environment Network (IPEN) adult project, self-reported data were taken from 13,745 adults (18-65 years) living in physically and socially diverse neighborhoods in 17 cities across 12 countries. Neighborhood perceptions were measured using the Neighborhood Environment Walkability Scale, and walking and cycling for transport were measured using the International Physical Activity Questionnaire-Long Form. Generalized additive mixed models were used to model walking or cycling for transport during the last seven days with neighborhood perceptions. Interactions by city were explored. RESULTS: Walking-for-transport outcomes were significantly associated with perceived residential density, land use mix-access, street connectivity, aesthetics, and safety. Any cycling for transport was significantly related to perceived land use mix-access, street connectivity, infrastructure, aesthetics, safety, and perceived distance to destinations. Between-city differences existed for some attributes in relation to walking or cycling for transport. CONCLUSIONS: Many perceived environmental attributes supported both cycling and walking; however, highly walkable environments may not support cycling for transport. People appear to walk for transport despite safety concerns. These findings can guide the implementation of global health strategies.

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In this paper, we compare the effectiveness of widely used approaches for representation of facial features in face images. Feature extraction is performed on face images for representation of four facial attributes, namely gender, age, race, and expression, by using discrete wavelet transform (DWT), Gabor wavelet, scale-invariant feature transform, local binary pattern (LBP), and Eigenfaces. After feature extraction and dimension reduction, demographic and expression classification is performed to identify the most discriminating techniques for representation of facial features. Extensive experiments are performed using publicly available face databases, namely Yale, Face95 Essex, and Cohn-Kanade (CK+) databases. Experimental results show that DWT, LBP, and Gabor wavelet methods are robust to variations of illumination, facial expression, and geometric transformations. Experimental results also show that race and expression are more difficult to predict than gender and age.

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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 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.