Portfolio-optimization models for small investors

Since 2010, the client base of online-trading service providers has grown significantly. Such companies enable small investors to access the stock market at advantageous rates. Because small investors buy and sell stocks in moderate amounts, they should consider fixed transaction costs, integral transaction units, and dividends when selecting their portfolio. In this paper, we consider the small investor’s problem of investing capital in stocks in a way that maximizes the expected portfolio return and guarantees that the portfolio risk does not exceed a prescribed risk level. Portfolio-optimization models known from the literature are in general designed for institutional investors and do not consider the specific constraints of small investors. We therefore extend four well-known portfolio-optimization models to make them applicable for small investors. We consider one nonlinear model that uses variance as a risk measure and three linear models that use the mean absolute deviation from the portfolio return, the maximum loss, and the conditional value-at-risk as risk measures. We extend all models to consider piecewise-constant transaction costs, integral transaction units, and dividends. In an out-of-sample experiment based on Swiss stock-market data and the cost structure of the online-trading service provider Swissquote, we apply both the basic models and the extended models; the former represent the perspective of an institutional investor, and the latter the perspective of a small investor. The basic models compute portfolios that yield on average a slightly higher return than the portfolios computed with the extended models. However, all generated portfolios yield on average a higher return than the Swiss performance index. There are considerable differences between the four risk measures with respect to the mean realized portfolio return and the standard deviation of the realized portfolio return.

Evaluation of coughing and nasal discharge as early indicators for an increased risk to develop equine recurrent airway obstruction (RAO).

BACKGROUND It is often assumed that horses with mild respiratory clinical signs, such as mucous nasal discharge and occasional coughing, have an increased risk of developing recurrent airway obstruction (RAO). HYPOTHESIS Compared to horses without any clinical signs of respiratory disease, those with occasional coughing, mucous nasal discharge, or both have an increased risk of developing signs of RAO (frequent coughing, increased breathing effort, exercise intolerance, or a combination of these) as characterized by the Horse Owner Assessed Respiratory Signs Index (HOARSI 1-4). ANIMALS Two half-sibling families descending from 2 RAO-affected stallions (n = 65 and n = 47) and an independent replication population of unrelated horses (n = 88). METHODS In a retrospective cohort study, standardized information on occurrence and frequency of coughing, mucous nasal discharge, poor performance, and abnormal breathing effort-and these factors combined in the HOARSI-as well as management factors were collected at intervals of 1.3-5 years. RESULTS Compared to horses without clinical signs of respiratory disease (half-siblings 7%; unrelated horses 3%), those with mild respiratory signs developed clinical signs of RAO more frequently: half-siblings with mucous nasal discharge 35% (P < .001, OR: 7.0, sensitivity: 62%, specificity: 81%), with mucous nasal discharge and occasional coughing 43% (P < .001, OR: 9.9, sensitivity: 55%, specificity: 89%); unrelated horses with occasional coughing: 25% (P = .006, OR = 9.7, sensitivity: 75%, specificity: 76%). CONCLUSIONS AND CLINICAL IMPORTANCE Occasional coughing and mucous nasal discharge might represent an increased risk of developing RAO.

Implications of Imaging Criteria for the Management and Treatment of Intraductal Papillary Mucinous Neoplasms - Benign versus Malignant Findings

OBJECTIVES Evaluation of computed tomography (CT) and magnetic resonance imaging (MRI) for differentiation of pancreatic intraductal papillary mucinous neoplasm (IPMN) subtypes based on objective imaging criteria. METHODS Fifty-eight patients with 60 histologically confirmed IPMNs were included in this retrospective study. Eighty-three imaging studies (CT,n = 42; MRI,n = 41) were analysed by three independent blinded observers (O1-O3), using established imaging criteria to assess likelihood of malignancy (-5, very likely benign; 5, very likely malignant) and histological subtype (i.e., low-grade (LGD), moderate-grade (MGD), high-grade dysplasia (HGD), early invasive carcinoma (IPMC), solid carcinoma (CA) arising from IPMN). RESULTS Forty-one benign (LGD IPMN,n = 20; MGD IPMN,n = 21) and 19 malignant (HGD IPMN,n = 3; IPMC,n = 6; solid CA,n = 10) IPMNs located in the main duct (n = 6), branch duct (n = 37), or both (n = 17) were evaluated. Overall accuracy of differentiation between benign and malignant IPMNs was 86/92 % (CT/MRI). Exclusion of overtly malignant cases (solid CA) resulted in overall accuracy of 83/90 % (CT/MRI). The presence of mural nodules and ductal lesion size ≥30 mm were significant indicators of malignancy (p = 0.02 and p < 0.001, respectively). CONCLUSIONS Invasive IPMN can be identified with high confidence and sensitivity using CT and MRI. The diagnostic problem that remains is the accurate radiological differentiation of premalignant and non-invasive subtypes. KEY POINTS • CT and MRI can differentiate benign from malignant forms of IPMN. • Identifying (pre)malignant histological IPMN subtypes by CT and MRI is difficult. • Overall, diagnostic performance with MRI was slightly (not significantly) superior to CT.

Service level agreements-driven management of distributed applications in cloud computing environments

Advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing workload conditions, such as number of connected users, application performance might suffer, leading to violations of Service Level Agreements (SLA) and possible inefficient use of hardware resources. Combining dynamic application requirements with the increased use of virtualised computing resources creates a challenging resource Management context for application and cloud-infrastructure owners. In such complex environments, business entities use SLAs as a means for specifying quantitative and qualitative requirements of services. There are several challenges in running distributed enterprise applications in cloud environments, ranging from the instantiation of service VMs in the correct order using an adequate quantity of computing resources, to adapting the number of running services in response to varying external loads, such as number of users. The application owner is interested in finding the optimum amount of computing and network resources to use for ensuring that the performance requirements of all her/his applications are met. She/he is also interested in appropriately scaling the distributed services so that application performance guarantees are maintained even under dynamic workload conditions. Similarly, the infrastructure Providers are interested in optimally provisioning the virtual resources onto the available physical infrastructure so that her/his operational costs are minimized, while maximizing the performance of tenants’ applications. Motivated by the complexities associated with the management and scaling of distributed applications, while satisfying multiple objectives (related to both consumers and providers of cloud resources), this thesis proposes a cloud resource management platform able to dynamically provision and coordinate the various lifecycle actions on both virtual and physical cloud resources using semantically enriched SLAs. The system focuses on dynamic sizing (scaling) of virtual infrastructures composed of virtual machines (VM) bounded application services. We describe several algorithms for adapting the number of VMs allocated to the distributed application in response to changing workload conditions, based on SLA-defined performance guarantees. We also present a framework for dynamic composition of scaling rules for distributed service, which used benchmark-generated application Monitoring traces. We show how these scaling rules can be combined and included into semantic SLAs for controlling allocation of services. We also provide a detailed description of the multi-objective infrastructure resource allocation problem and various approaches to satisfying this problem. We present a resource management system based on a genetic algorithm, which performs allocation of virtual resources, while considering the optimization of multiple criteria. We prove that our approach significantly outperforms reactive VM-scaling algorithms as well as heuristic-based VM-allocation approaches.

Critical indicators associated with negative performance in a selectively manned unit

Introduction. Selectively manned units have a long, international history, both military and civilian. Some examples include SWAT teams, firefighters, the FBI, the DEA, the CIA, and military Special Operations. These special duty operators are individuals who perform a highly skilled and dangerous job in a unique environment. A significant amount of money is spent by the Department of Defense (DoD) and other federal agencies to recruit, select, train, equip and support these operators. When a critical incident or significant life event occurs, that jeopardizes an operator's performance; there can be heavy losses in terms of training, time, money, and potentially, lives. In order to limit the number of critical incidents, selection processes have been developed over time to “select out” those individuals most likely to perform below desired performance standards under pressure or stress and to "select in" those with the "right stuff". This study is part of a larger program evaluation to assess markers that identify whether a person will fail under the stresses in a selectively manned unit. The primary question of the study is whether there are indicators in the selection process that signify potential negative performance at a later date. ^ Methods. The population being studied included applicants to a selectively manned DoD organization between 1993 and 2001 as part of a unit assessment and selection process (A&S). Approximately 1900 A&S records were included in the analysis. Over this nine year period, seventy-two individuals were determined to have had a critical incident. A critical incident can come in the form of problems with the law, personal, behavioral or family problems, integrity issues, and skills deficit. Of the seventy-two individuals, fifty-four of these had full assessment data and subsequent supervisor performance ratings which assessed how an individual performed while on the job. This group was compared across a variety of variables including demographics and psychometric testing with a group of 178 individuals who did not have a critical incident and had been determined to be good performers with positive ratings by their supervisors.^ Results. In approximately 2004, an online pre-screen survey was developed in the hopes of preselecting out those individuals with items that would potentially make them ineligible for selection to this organization. This survey has aided the organization to increase its selection rates and save resources in the process. (Patterson, Howard Smith, & Fisher, Unit Assessment and Selection Project, 2008) When the same prescreen was used on the critical incident individuals, it was found that over 60% of the individuals would have been flagged as unacceptable. This would have saved the organization valuable resources and heartache.^ There were some subtle demographic differences between the two groups (i.e. those with critical incidents were almost twice as likely to be divorced compared with the positive performers). Upon comparison of Psychometric testing several items were noted to be different. The two groups were similar when their IQ levels were compared using the Multidimensional Aptitude Battery (MAB). When looking at the Minnesota Multiphasic Personality Inventory (MMPI), there appeared to be a difference on the MMPI Social Introversion; the Critical Incidence group scored somewhat higher. When analysis was done, the number of MMPI Critical Items between the two groups was similar as well. When scores on the NEO Personality Inventory (NEO) were compared, the critical incident individuals tended to score higher on Openness and on its subscales (Ideas, Actions, and Feelings). There was a positive correlation between Total Neuroticism T Score and number of MMPI critical items.^ Conclusions. This study shows that the current pre-screening process is working and would have saved the organization significant resources. ^ If one was to develop a profile of a candidate who potentially could suffer a critical incident and subsequently jeopardize the unit, mission and the safety of the public they would look like the following: either divorced or never married, score high on the MMPI in Social Introversion, score low on MMPI with an "excessive" amount of MMPI critical items; and finally scores high on the NEO Openness and subscales Ideas, Feelings, and Actions.^ Based on the results gleaned from the analysis in this study there seems to be several factors, within psychometric testing, that when taken together, will aid the evaluators in selecting only the highest quality operators in order to save resources and to help protect the public from unfortunate critical incidents which may adversely affect our health and safety.^

The relationship between hospital financial performance and information technology integration strategy selection

In light of the new healthcare regulations, hospitals are increasingly reevaluating their IT integration strategies to meet expanded healthcare information exchange requirements. Nevertheless, hospital executives do not have all the information they need to differentiate between the available strategies and recognize what may better fit their organizational needs. ^ In the interest of providing the desired information, this study explored the relationships between hospital financial performance, integration strategy selection, and strategy change. The integration strategies examined – applied as binary logistic regression dependent variables and in the order from most to least integrated – were Single-Vendor (SV), Best-of-Suite (BoS), and Best-of-Breed (BoB). In addition, the financial measurements adopted as independent variables for the models were two administrative labor efficiency and six industry standard financial ratios designed to provide a broad proxy of hospital financial performance. Furthermore, descriptive statistical analyses were carried out to evaluate recent trends in hospital integration strategy change. Overall six research questions were proposed for this study. ^ The first research question sought to answer if financial performance was related to the selection of integration strategies. The next questions, however, explored whether hospitals were more likely to change strategies or remain the same when there was no external stimulus to change, and if they did change, they would prefer strategies closer to the existing ones. These were followed by a question that inquired if financial performance was also related to strategy change. Nevertheless, rounding up the questions, the last two probed if the new Health Information Technology for Economic and Clinical Health (HITECH) Act had any impact on the frequency and direction of strategy change. ^ The results confirmed that financial performance is related to both IT integration strategy selection and strategy change, while concurred with prior studies that suggested hospital and environmental characteristics are associated factors as well. Specifically this study noted that the most integrated SV strategy is related to increased administrative labor efficiency and the hybrid BoS strategy is associated with improved financial health (based on operating margin and equity financing ratios). On the other hand, no financial indicators were found to be related to the least integrated BoB strategy, except for short-term liquidity (current ratio) when involving strategy change. ^ Ultimately, this study concluded that when making IT integration strategy decisions hospitals closely follow the resource dependence view of minimizing uncertainty. As each integration strategy may favor certain organizational characteristics, hospitals traditionally preferred not to make strategy changes and when they did, they selected strategies that were more closely related to the existing ones. However, as new regulations further heighten revenue uncertainty while require increased information integration, moving forward, as evidence already suggests a growing trend of organizations shifting towards more integrated strategies, hospitals may be more limited in their strategy selection choices.^

A Methodological model to assist the optimization and risk management of mining investment decisions

Identifying, quantifying, and minimizing technical risks associated with investment decisions is a key challenge for mineral industry decision makers and investors. However, risk analysis in most bankable mine feasibility studies are based on the stochastic modelling of project “Net Present Value” (NPV)which, in most cases, fails to provide decision makers with a truly comprehensive analysis of risks associated with technical and management uncertainty and, as a result, are of little use for risk management and project optimization. This paper presents a value-chain risk management approach where project risk is evaluated for each step of the project lifecycle, from exploration to mine closure, and risk management is performed as a part of a stepwise value-added optimization process.

Performance optimization in switched reluctance motor drives

In this paper, switched reluctance motors (SRM) are proposed as an alternative for electric power assisted steering (EPAS) applications. A prototype machine has been developed as very attractive design for a steering electric motor, both from a cost and size perspective. A fourphase 8/6 SRM drive is designed for a rack type EPAS which should provide a maximum force of 10 kN. Two-dimension finite element analysis is used to validate the design.

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.

GreenDisc: a HW/SW energy optimization framework in globally distributed computation

In recent future, wireless sensor networks (WSNs) will experience a broad high-scale deployment (millions of nodes in the national area) with multiple information sources per node, and with very specific requirements for signal processing. In parallel, the broad range deployment of WSNs facilitates the definition and execution of ambitious studies, with a large input data set and high computational complexity. These computation resources, very often heterogeneous and driven on-demand, can only be satisfied by high-performance Data Centers (DCs). The high economical and environmental impact of the energy consumption in DCs requires aggressive energy optimization policies. These policies have been already detected but not successfully proposed. In this context, this paper shows the following on-going research lines and obtained results. In the field of WSNs: energy optimization in the processing nodes from different abstraction levels, including reconfigurable application specific architectures, efficient customization of the memory hierarchy, energy-aware management of the wireless interface, and design automation for signal processing applications. In the field of DCs: energy-optimal workload assignment policies in heterogeneous DCs, resource management policies with energy consciousness, and efficient cooling mechanisms that will cooperate in the minimization of the electricity bill of the DCs that process the data provided by the WSNs.

Riding out of the storm: How to deal with the complexity of grid and cloud management

Over the last decade, Grid computing paved the way for a new level of large scale distributed systems. This infrastructure made it possible to securely and reliably take advantage of widely separated computational resources that are part of several different organizations. Resources can be incorporated to the Grid, building a theoretical virtual supercomputer. In time, cloud computing emerged as a new type of large scale distributed system, inheriting and expanding the expertise and knowledge that have been obtained so far. Some of the main characteristics of Grids naturally evolved into clouds, others were modified and adapted and others were simply discarded or postponed. Regardless of these technical specifics, both Grids and clouds together can be considered as one of the most important advances in large scale distributed computing of the past ten years; however, this step in distributed computing has came along with a completely new level of complexity. Grid and cloud management mechanisms play a key role, and correct analysis and understanding of the system behavior are needed. Large scale distributed systems must be able to self-manage, incorporating autonomic features capable of controlling and optimizing all resources and services. Traditional distributed computing management mechanisms analyze each resource separately and adjust specific parameters of each one of them. When trying to adapt the same procedures to Grid and cloud computing, the vast complexity of these systems can make this task extremely complicated. But large scale distributed systems complexity could only be a matter of perspective. It could be possible to understand the Grid or cloud behavior as a single entity, instead of a set of resources. This abstraction could provide a different understanding of the system, describing large scale behavior and global events that probably would not be detected analyzing each resource separately. In this work we define a theoretical framework that combines both ideas, multiple resources and single entity, to develop large scale distributed systems management techniques aimed at system performance optimization, increased dependability and Quality of Service (QoS). The resulting synergy could be the key 350 J. Montes et al. to address the most important difficulties of Grid and cloud management.

Coal purchase optimization: a review from Spain

The study addresses the need to manage the risk of the purchase price of coal in a power company by changing the management model of the purchasing department. It eliminates the risk of price reduces the cost of buying coal and optimizing the performance of all electricity generation plants belonging to the company. You get more flexibility and optionallity to gain additional benefits both economic and efficiency in the supply to our generation fleet. The tools to achieve the above purpose will be financial derivatives that will be used as elements of management and not as mere speculation in the markets.

GreenDisc: a HW/SW energy optimization framework in globally distributed computation

In recent future, wireless sensor networks ({WSNs}) will experience a broad high-scale deployment (millions of nodes in the national area) with multiple information sources per node, and with very specific requirements for signal processing. In parallel, the broad range deployment of {WSNs} facilitates the definition and execution of ambitious studies, with a large input data set and high computational complexity. These computation resources, very often heterogeneous and driven on-demand, can only be satisfied by high-performance Data Centers ({DCs}). The high economical and environmental impact of the energy consumption in {DCs} requires aggressive energy optimization policies. These policies have been already detected but not successfully proposed. In this context, this paper shows the following on-going research lines and obtained results. In the field of {WSNs}: energy optimization in the processing nodes from different abstraction levels, including reconfigurable application specific architectures, efficient customization of the memory hierarchy, energy-aware management of the wireless interface, and design automation for signal processing applications. In the field of {DCs}: energy-optimal workload assignment policies in heterogeneous {DCs}, resource management policies with energy consciousness, and efficient cooling mechanisms that will cooperate in the minimization of the electricity bill of the DCs that process the data provided by the WSNs.