Knowledge Management and Leadership in the Higher Education: A First Approach

Today, it is more and more important to develop competences in the learning process of the university students (that is to say, to acquire knowledge but also skills, abilities, attitudes and values). This is because professional practice requires that the future graduates design and market products, defend the interests of their clients, be introduced in the Administration or, even, in the Politics. Universities must form professionals that become social and opinion leaders, consultants, advisory, entrepreneurs and, in short, people with capacity to solve problems. This paper offers a tool to evaluate the application for the professor of different styles of management in the process of the student’s learning. Its main contribution consists on advancing toward the setting in practice of a model that overcomes the limitations of the traditional practices based on the masterful class, and that it has been applied in Portugal and Spain.

Knowledge Management and Information Systems based on Workflow Technology

Knowledge management is critical for the success of virtual communities, especially in the case of distributed working groups. A representative example of this scenario is the distributed software development, where it is necessary an optimal coordination to avoid common problems such as duplicated work. In this paper the feasibility of using the workflow technology as a knowledge management system is discussed, and a practical use case is presented. This use case is an information system that has been deployed within a banking environment. It combines common workflow technology with a new conception of the interaction among participants through the extension of existing definition languages.

Exploiting Structured Linked Data in Enterprise Knowledge Management Systems: An Idea Management Case Study

In parallel to the effort of creating Open Linked Data for the World Wide Web there is a number of projects aimed for developing the same technologies but in the context of their usage in closed environments such as private enterprises. In the paper, we present results of research on interlinking structured data for use in Idea Management Systems - a still rare breed of knowledge management systems dedicated to innovation management. In our study, we show the process of extending an ontology that initially covers only the Idea Management System structure towards the concept of linking with distributed enterprise data and public data using Semantic Web technologies. Furthermore we point out how the established links can help to solve the key problems of contemporary Idea Management Systems

Influence of nutritional and management practices on productive performance and egg quality of brown egg-laying hens = Influencia de factores nutricionales y de manejo sobre la productividad y calidad del huevo en gallinas ponedoras rubias

El objetivo general de esta Tesis Doctoral fue estudiar la influencia de diversos factores nutricionales y de manejo sobre la productividad y la calidad del huevo en gallinas ponedoras comerciales rubias. Los factores estudiados fueron: 1) Cereal principal y tipo de grasa en la dieta; 2) Nivel de proteína bruta y grasa en la dieta; 3) Nivel energético de la dieta; 4) Peso vivo al inicio del período de puesta. En el experimento 1, la influencia del cereal principal en la dieta y el tipo de grasa suplementada en la dieta sobre los parámetros productivos y la calidad del huevo fue estudiado en 756 gallinas rubias de la estirpe Lohmann desde la sem 22 hasta las 54 de vida. El experimento se realizó mediante un diseño completamente al azar con 9 tratamientos ordenados factorialmente, con 3 cereales bases (maíz, trigo blando y cebada) y 3 tipos de grasa que variaban en su contenido en ácido linoléico (aceite de soja, oleína vegetal mezcla y manteca). Todas las dietas satisfacian las recomendaciones nutricionales para gallinas ponedoras rubias según el NRC (1994) y FEDNA (2008). La unidad experimental fue la jaula para todas las variables. Cada tratamiento fue replicado 4 veces, y la unidad experimental estuvo formada por 21 gallinas alojadas en grupos de 7. Las dietas fueron formuladas con un contenido nutritivo similar, excepto para el ácido linoléico, que varió en función del tipo de cereal y grasa utilizado. Así, dependiendo de la combinación de estos elementos el contenido de este ácido graso varió desde un 0.8% (dieta trigo-manteca) a un 3.4% (dieta maíz-aceite de soja). Este rango de ácido linoléico permitió estimar el nivel mínimo de este nutriente en el pienso que permite maximizar el peso del huevo. Los parámetros productivos y la calidad del huevo se controlaron cada 28 días y el peso de las aves se midió individualmente al inicio y al final del experimento con el objetivo de estudiar la variación en el peso vivo de los animales. No se observaron interacciones entre el tipo de cereal y grasa en la dieta para ninguna de las variables productivas estudiadas. Los tratamientos experimentales no afectaron a las principales variables productivas (porcentaje de puesta, peso del huevo y masa de huevo). Sin embargo, la ganancia de peso fue mayor en gallinas alimentadas con maíz o trigo que las gallinas alimentadas con cebada (243 vs. 238 vs. 202 g, respectivamente; P< 0.05). En el mismo sentido, las gallinas alimentadas con manteca obtuvieron una mayor ganancia de peso que las gallinas alimentadas con aceite de soja u oleína vegetal (251 vs. 221 vs. 210 g, respectivamente; P< 0.05). En cuanto a las variables estudiadas en relación con la calidad del huevo, ninguna de las variables estudiadas se vio afectada por el tratamiento experimental, salvo la pigmentación de la yema. Así, las gallinas alimentadas con maíz como cereal principal obtuvieron una mayor puntuación en relación con la escala de color que las gallinas alimentadas con trigo y con cebada (9.0 vs. 8.3 vs. 8.3, respectivamente; P< 0.001). La pigmentación de la yema también se vio afectada por el tipo de grasa en la dieta, así, las gallinas alimentadas con manteca obtuvieron una mayor puntuación de color en relación con la escala de color que las gallinas alimentadas con aceite de soja u oleína vegetal (8.9 vs. 8.5 vs. 8.2, respectivamente; P< 0.001). La influencia del contenido en ácido linoléico respecto al peso de huevo y masa de huevo fue mayor a medida que el contenido de dicho ácido graso se redujo en la dieta. Así, la influencia de la dieta en los radios peso de huevo/g linoléico ingerido y masa de huevo/g linoléico ingerido fue significativamente mayor a medida que el contenido en dicho ácido graso disminuyo en la dieta (P< 0.001). Los resultados del ensayo indican que las gallinas ponedoras rubias no necesitan más de un 1.0% de ácido linoléico en la dieta para maximizar la producción y el tamaño del huevo. Además, se pudo concluir que los 3 cereales y las 3 grasas utilizadas pueden sustituirse en la dieta sin ningún perjuicio productivo o referente a la calidad del huevo siempre que los requerimientos de los animales sean cubiertos. En el experimento 2, la influencia del nivel de proteína bruta y el contenido de grasa de la dieta sobre los parámetros productivos y la calidad del huevo fue estudiado en 672 gallinas ponedoras rubias de la estirpe Lohmann entre las sem 22 y 50 de vida. El experimento fue conducido mediante un diseño completamente al azar con 8 tratamientos ordenados factorialmente con 4 dietas y 2 pesos vivos distintos al inicio de puesta (1592 vs. 1860g). Tres de esas dietas diferían en el contenido de proteína bruta (16.5%, 17.5% y 18.5%) y tenían un contenido en grasa añadida de 1.8%. La cuarta dieta tenía el nivel proteico más elevado (18.5%) pero fue suplementada con 3.6% de grasa añadida en vez de 1.8%. Cada tratamiento fue replicado 4 veces y la unidad experimental consistió en 21 gallinas alojadas dentro de grupos de 7 animales en 3 jaulas contiguas. Todas las dietas fueron isocalóricas (2750 kcal EMAn/kg) y cubrieron las recomendaciones en aminoácidos para gallinas ponedoras rubias (Arg, Ile, Lys, Met, Thr, Trp, TSAA y Val) según el NRC (1994) y FEDNA (2008). Los efectos de los tratamientos sobre las variables productivas y la calidad de huevo fueron estudiados cada 28 días. La dieta no afecto a ninguna de las variables productivas estudiadas a lo largo del período productivo. Sin embargo, el peso inicial origino que las gallinas pesadas consumieran más (120.6 vs. 113.9 g; P< 0.001), obtuvieran un porcentaje de puesta mayor (92.5 vs. 89.8%; P< 0.01) y un peso del huevo mayor (64.9 vs. 62.4 g; P< 0.001) que las gallinas ligeras. El peso inicial de las gallinas no afecto al IC por kg de huevo ni a la mortalidad, sin embargo, la ganancia de peso fue mayor (289 vs. 233 g; P< 0.01) y el IC por docena de huevos fue mejor (1.52 vs. 1.57; P< 0.01) en las gallinas ligeras que en las gallinas pesadas. En cuanto a la calidad del huevo, la dieta no influyó sobre ninguna de las variables estudiadas. Los resultados del ensayo muestran que las gallinas ponedoras rubias, independientemente de su peso vivo al inicio de la puesta, no necesitan una cantidad de proteína bruta superior a 16.5% para maximizar la producción, asegurando que las dietas cubren los requerimientos en AA indispensables. Asimismo, se puedo concluir que las gallinas con un peso más elevado al inicio de puesta producen más masa de huevo que las gallinas con un peso más bajo debido a que las primeras producen más cantidad de huevos y más pesados. Sin embargo, ambos grupos de peso obtuvieron el mismo IC por kg de huevo y las gallinas más livianas en peso obtuvieron un mejor IC por docena de huevo que las pesadas. En el experimento 3 la influencia de la concentración energética sobre los parámetros productivos y la calidad del huevo fue estudiada en 520 gallinas ponedoras rubias de la estirpe Hy-Line en el período 24-59 sem de vida. Se utilizaron 8 tratamientos ordenados factorialmente con 4 dietas que variaron en el contenido energético (2650, 2750, 2850 y 2950 kcal EMAn/kg) y 2 pesos vivos distintos al inicio del período de puesta (1733 vs. 1606g). Cada tratamiento fue replicado 5 veces y la unidad experimental consistió en una jaula con 13 aves. Todas las dietas se diseñaron para que tuvieran una concentración nutritiva similar por unidad energética. Las variables productivas y de calidad de huevo se estudiaron mediante controles cada 28 días desde el inicio del experimento. No se observaron interacciones entre el nivel energético y el peso inicial del ave para ninguna de las variables estudiadas. Un incremento en la concentración energética de la dieta incrementó la producción de huevos (88.8 % vs. 91.2 % vs. 92.7 % vs. 90.5 %), masa de huevo (56.1 g/d vs. 58.1 g/d vs. 58.8 g/d vs. 58.1 g/d), y eficiencia energética (5.42 vs. 5.39 vs. 5.38 vs. 5.58 kcal EMA/g huevo) de forma lineal y cuadrática (P< 0.05) y afectó significativamente a la ganancia de peso (255 g vs. 300 g vs. 325 g vs. 359 g; P<0.05) . Sin embargo, un incremento en la concentración energética provocó un descenso lineal en el consumo de los animales (115 g vs. 114 g vs. 111 g vs. 110 g; P< 0.001) y un descenso lineal y cuadrático en el IC por kg de huevo (2.05 vs. 1.96 vs. 1.89 vs. 1.89; P< 0.01). En cuanto a la calidad del huevo, un incremento en el contenido energético de la dieta provocó una reducción en la calidad del albumen de forma lineal en forma de reducción de Unidades Haugh (88.4 vs. 87.8 vs. 86.3 vs. 84.7; P< 0.001), asimismo el incremento de energía redujo de forma lineal la proporción relativa de cáscara en el huevo (9.7 vs. 9.6 vs. 9.6 vs. 9.5; P< 0.001). Sin embargo, el incremento energético propició un incremento lineal en la pigmentación de la yema del huevo (7.4 vs. 7.4 vs. 7.6 vs. 7.9; P< 0.001). El peso vivo al inicio de la prueba afecto a las variables productivas y a la calidad del huevo. Así, los huevos procedentes de gallinas pesadas al inicio de puesta tuvieron una mayor proporción de yema (25.7 % vs. 25.3 %; P< 0.001) y menor de albumen (64.7 vs. 65.0; P< 0.01) y cáscara (9.5 vs. 9.6; P< 0.05) respecto de los huevos procedentes de gallinas ligeras. Consecuentemente, el ratio yema:albumen fue mayor (0.40 vs. 0.39; P< 0.001) para las gallinas pesadas. Según los resultados del experimento se pudo concluir que las actuales gallinas ponedoras rubias responden con incrementos en la producción y en la masa del huevo a incrementos en la concentración energética hasta un límite que se sitúa en 2850 kcal EMAn/kg. Asimismo, los resultados obtenidos entre los 2 grupos de peso al inicio de puesta demostraron que las gallinas pesadas al inicio de puesta tienen un mayor consumo y producen huevos más pesados, con el consecuente aumento de la masa del huevo respecto de gallinas más ligeras. Sin embargo, el IC por kg de huevo fue el mismo en ambos grupos de gallinas y el IC por docena de huevo fue mejor en las gallinas ligeras. Asimismo, la eficiencia energética fue mejor en las gallinas ligeras. Abstract The general aim of this PhD Thesis was to study the influence of different nutritional factors and management on the productivity and egg quality of comercial Brown laying hens. The factor studied were: 1) The effect of the main cereal and type of fat of the diet; 2) The effect of crude protein and fat content of the diet; 3) The effect of energy concentration of the diet; 4) The effect of initial body weight of the hens at the onset of lay period. In experiment 1, the influence of the main cereal and type of supplemental fat in the diet on productive performance and egg quality of the eggs was studied in 756 Lohmann brown-egg laying hens from 22 to 54 wk of age. The experiment was conducted as a completely randomized design with 9 treatments arranged factorially with 3 cereals (dented corn, soft wheat, and barley) and 3 types of fat (soy oil, acidulated vegetable soapstocks, and lard). Each treatment was replicated 4 times (21 hens per replicate). All diets were formulated according to NRC (1994) and FEDNA (2008) to have similar nutrient content except for linoleic acid that ranged from 0.8 (wheat-lard diet) to 3.4% (corn-soy bean oil) depending on the combination of cereal and fat source used. This approach will allow to estimate the minimum level of linoleic acid in the diets that maximizes egg weight. Productive performance and egg quality traits were recorded every 28 d and BW of the hens was measured individually at the beginning and at the end of the experiment. No significant interactions between main factors were detected for any of the variables studied. Egg production, egg weight, and egg mass were not affected by dietary treatment. Body weight gain was higher (243 vs. 238 vs. 202 g; P<0.05) for hens fed corn or wheat than for hens fed barley and also for hens fed lard than for hens fed soy oil or acidulated vegetable soapstocks (251 vs. 221 vs. 210 g; P< 0.05). Egg quality was not influenced by dietary treatment except for yolk color that was greater (9.0 vs. 8.3 vs. 8.3; P< 0.001) for hens fed corn than for hens fed wheat or barley and for hens fed lard than for hens fed soy oil or acidulated vegetable soapstocks (8.9 vs. 8.5 vs. 8.2, respectivamente; P< 0.001). The influence of linoleic acid on egg weight and egg mass was higher when the fatty acid was reduced in the diet. Thus, the influence of the diet in egg weight/g linoleic acid intake and egg mass/g linolec acid intake was higher when the amount of this fatty acid decreased in the diet (P< 0.001). It is concluded that brown egg laying hens do not need more than 1.0% of linoleic acid in the diet (1.16 g/hen/d) to maximize egg production and egg size. The 3 cereals and the 3 fat sources tested can replace each other in the diet provided that the linoleic acid requirements to maximize egg size are met. In experiment 2, the influence of CP and fat content of the diet on performance and egg quality traits was studied in 672 Lohmann brown egg-laying hens from 22 to 50 wk of age. The experiment was conducted as a completely randomized design with 8 treatments arranged factorially with 4 diets and 2 initial BW of the hens (1,592 vs. 1,860 g). Three of these diets differed in the CP content (16.5, 17.5, and 18.5%) and included 1.8% added fat. The fourth diet had also 18.5% CP but was supplemented with 3.6% fat instead of 1.8% fat. Each treatment was replicated 4 times and the experimental unit consisted of 21 hens allocated in groups of 7 in 3 adjacent cages. All diets were isocaloric (2,750 kcal AME/kg) and met the recommendations of brown egg-laying hens for digestible Arg, Ile, Lys, Met, Thr, Trp, TSAA, and Val. Productive performance and egg quality were recorded by replicate every 28-d. For the entire experimental period, diet did not affect any of the productive performance traits studied but the heavier hens had higher ADFI (120.6 vs. 113.9g; P< 0.001), egg production (92.5 vs. 89.8%; P< 0.01), and egg weight (64.9 vs. 62.4g; P< 0.001) than the lighter hens. Initial BW did not affect feed conversion per kilogram of eggs or hen mortality but BW gain was higher (289 vs. 233g; P< 0.01) and FCR per dozen of eggs was better (1.52 vs. 1.57; P< 0.01) for the lighter than for the heavier hens. None of the egg quality variables studied was affected by dietary treatment or initial BW of the hens. It is concluded that brown egg-laying hens, irrespective of their initial BW, do not need more than 16.5% CP to maximize egg production provided that the diet meet the requirements for key indispensable amino acids. Heavier hens produce more eggs that are larger than lighter hens but feed efficiency per kilogram of eggs is not affected. In experiment 3, the influence of AMEn concentration of the diet on productive performance and egg quality traits was studied in 520 Hy-Line brown egg-laying hens differing in initial BW from 24 to 59 wks of age. There were 8 treatments arranged factorially with 4 diets varying in energy content (2,650, 2,750, 2,850, and 2,950 kcal AMEn/kg) and 2 initial BW of the hens (1,733 vs. 1,606 g). Each treatment was replicated 5 times (13 hens per replicate) and all diets had similar nutrient content per unit of energy. No interactions between energy content of the diet and initial BW of the hens were detected for any trait. An increase in energy concentration of the diet increased (linear, P< 0.05; quadratic P< 0.05) egg production (88.8 % vs. 91.2 % vs. 92.7 % vs. 90.5 %), egg mass (56.1 g/d vs. 58.1 g/d vs. 58.8 g/d vs. 58.1 g/d), energy efficiency (5.42 vs. 5.39 vs. 5.38 vs. 5.58 kcal AMEn/g of egg), and BW gain (255 g vs. 300 g vs. 325 g vs. 359 g; P<0.05) but decreased ADFI (115 g vs. 114 g vs. 111 g vs. 110 g; P< linear, P< 0.001) and FCR per kg of eggs (2.05 vs. 1.96 vs. 1.89 vs. 1.89; linear, P< 0.01; quadratic P< 0.01). An increase in energy content of the diet reduced Haugh units (88.4 vs. 87.8 vs. 86.3 vs. 84.7; P< 0.01) and the proportion of shell in the egg (9.7 vs. 9.6 vs. 9.6 vs. 9.5; P< 0.001). Feed intake (114.6 vs. 111.1 g/hen per day), AMEn intake (321 vs. 311 kcal/hen per day), egg weight (64.2 vs. 63.0 g), and egg mass (58.5 vs. 57.0 g) were higher for the heavier than for the lighter hens (P<0.01) but FCR per kg of eggs and energy efficiency were not affected. Eggs from the heavier hens had higher proportion of yolk (25.7 % vs. 25.3 %; P< 0.001) and lower of albumen (64.7 vs. 65.0; P< 0.01) and shell (9.5 vs. 9.6; P< 0.05) than eggs from the lighter hens. Consequently, the yolk to albumen ratio was higher (0.40 vs. 0.39; P< 0.001) for the heavier hens. It is concluded that brown egg-laying hens respond with increases in egg production and egg mass, to increases in AMEn concentration of the diet up to 2,850 kcal/kg. Heavy hens had higher feed intake and produced heavier eggs and more egg mass than light hens. However, energy efficiency was better for the lighter hens.

Effects of different soil management practices on soil mechanic resistance and seed depth placement in a maize crop in Alentejo, Portugal Mediterranean region.

No tillage, minimum tillage and conventional tillage practices are commonly used in maize crops in Alentejo, affecting soil physic conditions and determining seeders performance. Seeders distribution can be evaluated in the longitudinal and vertical planes. Vertical plane is specified by seeding depth (Karayel et al., 2008). If, in one hand seeding depth uniformity is a goal for all crop establishment , in the other hand, seeders furrow openers depth control is never constant depending on soil conditions. Seed depth uniformity affects crop emergence, Liu et al. (2004) showed an higher correlation between crop productivity and emergence uniformity than with longitudinal plants distribution. Neto et al. (2007) evaluating seed depth placement by measuring maize mesocotyl length under no tillage conditions in 38 farms concluded that 20% of coefficient of variation suggests the need of improvement seeders depth control mechanisms. The objective of this study was to evaluate casual relationships and create spatial variability maps between soil mechanic resistance and vertical distribution under three different soil practices to improve seed depth uniformity.

The impact of sustainable construction and knowledge management on sustainability goals. A review of the venezuelan renewable energy sector

The recognition of the relevance of energy, especially of the renewable energies generated by the sun, water, wind, tides, modern biomass or thermal is growing significantly in the global society based on the possibility it has to improve societies′ quality of life, to support poverty reduction and sustainable development. Renewable energy, and mainly the energy generated by large hydropower generation projects that supply most of the renewable energy consumed by developing countries, requires many technical, legal, financial and social complex processes sustained by innovations and valuable knowledge. Besides these efforts, renewable energy requires a solid infrastructure to generate and distribute the energy resources needed to solve the basic needs of society. This demands a proper construction performance to deliver the energy projects planned according to specifications and respecting environmental and social concerns, which implies the observance of sustainable construction guidelines. But construction projects are complex and demanding and frequently face time and cost overruns that may cause negative impacts on the initial planning and thus on society. The renewable energy issue and the large renewable energy power generation and distribution projects are particularly significant for developing countries and for Latin America in particular, as this region concentrates an important hydropower potential and installed capacity. Using as references the performance of Venezuelan large hydropower generation projects and the Guri dam construction, this research evaluates the tight relationship existing between sustainable construction and knowledge management and their impact to achieve sustainability goals. The knowledge management processes are proposed as a basic strategy to allow learning from successes and failures obtained in previous projects and transform the enhancement opportunites into actions to improve the performance of the renewable energy power generation and distribution projects.

The Role of Knowledge Modeling Techniques in Software Development: A General Approach Based on a Knowledge Management Tool

The aim of the paper is to discuss the use of knowledge models to formulate general applications. First, the paper presents the recent evolution of the software field where increasing attention is paid to conceptual modeling. Then, the current state of knowledge modeling techniques is described where increased reliability is available through the modern knowledge acquisition techniques and supporting tools. The KSM (Knowledge Structure Manager) tool is described next. First, the concept of knowledge area is introduced as a building block where methods to perform a collection of tasks are included together with the bodies of knowledge providing the basic methods to perform the basic tasks. Then, the CONCEL language to define vocabularies of domains and the LINK language for methods formulation are introduced. Finally, the object oriented implementation of a knowledge area is described and a general methodology for application design and maintenance supported by KSM is proposed. To illustrate the concepts and methods, an example of system for intelligent traffic management in a road network is described. This example is followed by a proposal of generalization for reuse of the resulting architecture. Finally, some concluding comments are proposed about the feasibility of using the knowledge modeling tools and methods for general application design.

Fractal parameters of pore space from CT images of soils under contrasting management practices

Soil structure plays an important role in flow and transport phenomena, and a quantitative characterization of the spatial heterogeneity of the pore space geometry is beneficial for prediction of soil physical properties. Morphological features such as pore-size distribution, pore space volume or pore?solid surface can be altered by different soil management practices. Irregularity of these features and their changes can be described using fractal geometry. In this study, we focus primarily on the characterization of soil pore space as a 3D geometrical shape by fractal analysis and on the ability of fractal dimensions to differentiate between two a priori different soil structures. We analyze X-ray computed tomography (CT) images of soils samples from two nearby areas with contrasting management practices. Within these two different soil systems, samples were collected from three depths. Fractal dimensions of the pore-size distributions were different depending on soil use and averaged values also differed at each depth. Fractal dimensions of the volume and surface of the pore space were lower in the tilled soil than in the natural soil but their standard deviations were higher in the former as compared to the latter. Also, it was observed that soil use was a factor that had a statistically significant effect on fractal parameters. Fractal parameters provide useful complementary information about changes in soil structure due to changes in soil management. Read More: http://www.worldscientific.com/doi/abs/10.1142/S0218348X14400118?queryID=%24%7BresultBean.queryID%7D&