933 resultados para Strategy model


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Model predictive control (MPC) is usually implemented as a control strategy where the system outputs are controlled within specified zones, instead of fixed set points. One strategy to implement the zone control is by means of the selection of different weights for the output error in the control cost function. A disadvantage of this approach is that closed-loop stability cannot be guaranteed, as a different linear controller may be activated at each time step. A way to implement a stable zone control is by means of the use of an infinite horizon cost in which the set point is an additional variable of the control problem. In this case, the set point is restricted to remain inside the output zone and an appropriate output slack variable is included in the optimisation problem to assure the recursive feasibility of the control optimisation problem. Following this approach, a robust MPC is developed for the case of multi-model uncertainty of open-loop stable systems. The controller is devoted to maintain the outputs within their corresponding feasible zone, while reaching the desired optimal input target. Simulation of a process of the oil re. ning industry illustrates the performance of the proposed strategy.

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Accurate price forecasting for agricultural commodities can have significant decision-making implications for suppliers, especially those of biofuels, where the agriculture and energy sectors intersect. Environmental pressures and high oil prices affect demand for biofuels and have reignited the discussion about effects on food prices. Suppliers in the sugar-alcohol sector need to decide the ideal proportion of ethanol and sugar to optimise their financial strategy. Prices can be affected by exogenous factors, such as exchange rates and interest rates, as well as non-observable variables like the convenience yield, which is related to supply shortages. The literature generally uses two approaches: artificial neural networks (ANNs), which are recognised as being in the forefront of exogenous-variable analysis, and stochastic models such as the Kalman filter, which is able to account for non-observable variables. This article proposes a hybrid model for forecasting the prices of agricultural commodities that is built upon both approaches and is applied to forecast the price of sugar. The Kalman filter considers the structure of the stochastic process that describes the evolution of prices. Neural networks allow variables that can impact asset prices in an indirect, nonlinear way, what cannot be incorporated easily into traditional econometric models.

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Methylobacterium mesophilicum, originally isolated as an endophytic bacterium from citrus plants, was genetically transformed to express green fluorescent protein (GFP). The GFP-labeled strain of M. mesophilicum was inoculated into Catharanthus roseus (model plant) seedlings and further observed colonizing its xylem vessels. The transmission of this endophyte by Bucephalogonia xanthophis, one of the insect vectors that transmit Xylella fastidiosa subsp. pauca, was verified by insects feeding from fluids containing the GFP bacterium followed by transmission to plants and isolating the endophyte from C. roseus plants. Forty-five days after inoculation, the plants exhibited endophytic colonization by M. mesophilicum, confirming this bacterium as a nonpathogenic, xylem-associated endophyte. Our data demonstrate that M. mesophilicum not only occupy the same niche of X. fastidiosa subsp. pauca inside plants but also may be transmitted by B. xanthophis. The transmission, colonization, and genetic manipulation of M. mesophilicum is a prerequisite to examining the potential use of symbiotic control to interrupt the transmission of X. fastidiosa subsp. pauca, the bacterial pathogen causing Citrus variegated chlorosis by insect vectors.

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PGE(2), an arachidonic acid metabolite produced by various type of cells regulates a broad range of physiological activities in the endocrine, cardiovascular, gastrointestinal, and immune systems, and is involved in maintaining the local homeostasis. In the immune system, PGE(2) is mainly produced by APCs and it can suppress the Th1-mediated immune responses. The aim of this study was to develop PGE(2)-loaded biodegradable MS that prolong and sustain the in vivo release of this mediator. An o/w emulsion solvent extraction-evaporation method was chosen to prepare the MS. We determined their diameters, evaluated the in vitro release of PGE(2), using enzyme immunoassay and MS uptake by peritoneal macrophages. To assess the preservation of biological activities of this mediator, we determined the effect of PGE(2) released from MS on LPS-induced TNF-alpha release by murine peritoneal macrophages. We also analyzed the effect of encapsulated PGE(2) on inflammatory mediators release from HUVECs. Finally, we studied the effect of PGE(2) released from biodegradable MS in sepsis animal model. The use of this formulation can provide an alternative strategy for treating infections, by modulating or inhibiting inflammatory responses, especially when they constitute an exacerbated profile. (C) 2008 Elsevier B.V. All rights reserved.

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We re-mapped the soils of the Murray-Darling Basin (MDB) in 1995-1998 with a minimum of new fieldwork, making the most out of existing data. We collated existing digital soil maps and used inductive spatial modelling to predict soil types from those maps combined with environmental predictor variables. Lithology, Landsat Multi Spectral Scanner (Landsat MSS), the 9-s digital elevation model (DEM) of Australia and derived terrain attributes, all gridded to 250-m pixels, were the predictor variables. Because the basin-wide datasets were very large data mining software was used for modelling. Rule induction by data mining was also used to define the spatial domain of extrapolation for the extension of soil-landscape models from existing soil maps. Procedures to estimate the uncertainty associated with the predictions and quality of information for the new soil-landforms map of the MDB are described. (C) 2002 Elsevier Science B.V. All rights reserved.

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Protein engineering is a powerful tool, which correlates protein structure with specific functions, both in applied biotechnology and in basic research. Here, we present a practical teaching course for engineering the green fluorescent protein (GFP) from Aequorea victoria by a random mutagenesis strategy using error-prone polymerase chain reaction. Screening of bacterial colonies transformed with random mutant libraries identified GFP variants with increased fluorescence yields. Mapping the three-dimensional structure of these mutants demonstrated how alterations in structural features such as the environment around the fluorophore and properties of the protein surface can influence functional properties such as the intensity of fluorescence and protein solubility.

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Background Meta-analysis is increasingly being employed as a screening procedure in large-scale association studies to select promising variants for follow-up studies. However, standard methods for meta-analysis require the assumption of an underlying genetic model, which is typically unknown a priori. This drawback can introduce model misspecifications, causing power to be suboptimal, or the evaluation of multiple genetic models, which augments the number of false-positive associations, ultimately leading to waste of resources with fruitless replication studies. We used simulated meta-analyses of large genetic association studies to investigate naive strategies of genetic model specification to optimize screenings of genome-wide meta-analysis signals for further replication. Methods Different methods, meta-analytical models and strategies were compared in terms of power and type-I error. Simulations were carried out for a binary trait in a wide range of true genetic models, genome-wide thresholds, minor allele frequencies (MAFs), odds ratios and between-study heterogeneity (tau(2)). Results Among the investigated strategies, a simple Bonferroni-corrected approach that fits both multiplicative and recessive models was found to be optimal in most examined scenarios, reducing the likelihood of false discoveries and enhancing power in scenarios with small MAFs either in the presence or in absence of heterogeneity. Nonetheless, this strategy is sensitive to tau(2) whenever the susceptibility allele is common (MAF epsilon 30%), resulting in an increased number of false-positive associations compared with an analysis that considers only the multiplicative model. Conclusion Invoking a simple Bonferroni adjustment and testing for both multiplicative and recessive models is fast and an optimal strategy in large meta-analysis-based screenings. However, care must be taken when examined variants are common, where specification of a multiplicative model alone may be preferable.

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In this paper, we present a fuzzy approach to the Reed-Frost model for epidemic spreading taking into account uncertainties in the diagnostic of the infection. The heterogeneities in the infected group is based on the clinical signals of the individuals (symptoms, laboratorial exams, medical findings, etc.), which are incorporated into the dynamic of the epidemic. The infectivity level is time-varying and the classification of the individuals is performed through fuzzy relations. Simulations considering a real problem with data of the viral epidemic in a children daycare are performed and the results are compared with a stochastic Reed-Frost generalization.

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The purpose of this research was to evaluate educational strategies applied to a tele-education leprosy course. The curriculum was for members of the Brazilian Family Health Team and was made available through the Sao Paulo Telehealth Portal. The course educational strategy was based on a constructivist learning model where interactivity was emphasized. Authors assessed motivational aspects of the course using the WebMAC Professional tool. Forty-eight healthcare professionals answered the evaluation questionnaire. Adequate internal consistency was achieved (Cronbach`s alpha = 0.79). More than 95% of queried items received good evaluations. Multidimensional analysis according to motivational groups of questions (STIMULATING, MEANINGFUL, ORGANIZED, EASY-TO-USE) showed high agreement. According to WebMAC`s criteria, it was considered an ""awesome course."" The tele-educational strategies implemented for leprosy disclosed high motivational scores.

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The RAS (renin angiotensin system) is classically involved in BP (blood pressure) regulation and water electrolyte balance, and in the central nervous system it has been mostly associated with homoeostatic processes, such as thirst, hormone secretion and thermoregulation. Epilepsies are chronic neurological disorders characterized by recurrent epileptic seizures that affect 1-3% of the world`s population, and the most commonly used anticonvulsants are described to be effective in approx. 70% of the population with this neurological alteration. Using a rat model of epilepsy, we found that components of the RAS, namely ACE (angiotensin-converting enzyme) and the AT(1) receptor (angiotensin II type I receptor) are up-regulated in the brain (2.6- and 8.2-fold respectively) following repetitive seizures. Subsequently, epileptic animals were treated with clinically used doses of enalapril, an ACE inhibitor, and losartan, an AT(1) receptor blocker, leading to a significant decrease in seizure severities. These results suggest that centrally acting drugs that target the RAS deserve further investigation as possible anticonvulsant agents and may represent an additional strategy in the management of epileptic patients.

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In this study we present a novel automated strategy for predicting infarct evolution, based on MR diffusion and perfusion images acquired in the acute stage of stroke. The validity of this methodology was tested on novel patient data including data acquired from an independent stroke clinic. Regions-of-interest (ROIs) defining the initial diffusion lesion and tissue with abnormal hemodynamic function as defined by the mean transit time (MTT) abnormality were automatically extracted from DWI/PI maps. Quantitative measures of cerebral blood flow (CBF) and volume (CBV) along with ratio measures defined relative to the contralateral hemisphere (r(a)CBF and r(a)CBV) were calculated for the MTT ROIs. A parametric normal classifier algorithm incorporating these measures was used to predict infarct growth. The mean r(a)CBF and r(a)CBV values for eventually infarcted MTT tissue were 0.70 +/-0.19 and 1.20 +/-0.36. For recovered tissue the mean values were 0.99 +/-0.25 and 1.87 +/-0.71, respectively. There was a significant difference between these two regions for both measures (P

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The 101 residue protein early pregnancy factor (EPF), also known as human chaperonin 10, was synthesized from four functionalized, but unprotected, peptide segments by a sequential thioether ligation strategy. The approach exploits the differential reactivity of a peptide-NHCH2CH2SH thiolate with XCH2CO-peptides, where X = Cl or I/Br. Initial model studies with short functionalized (but unprotected) peptides showed a significantly faster reaction of a peptide-NHCH2CH2SH thiolate with a BrCH2CO-peptide than with a CICH2CO-peptide, where thiolate displacement of the halide leads to chemoselective formation of a thioether surrogate for the Gly-Gly peptide bond. This rate difference was used as the basis of a novel sequential ligation approach to the synthesis of large polypeptide chains. Thus, ligation of a model bifunctional N-alpha-chloroacetyl, C-terminal thiolated peptide with a second N-alpha-bromoacetyl peptide demonstrated chemoselective bromide displacement by the thiol group. Further investigations showed that the relatively unreactive N-alpha-chloroacetyl peptides could be activated by halide exchange using saturated KI solutions to yield the highly reactive No-iodoacetyl peptides. These findings were used to formulate a sequential thioether ligation strategy for the synthesis of EPF, a 101 amino acid protein containing three Gly-Gly sites approximately equidistantly spaced within the peptide chain. Four peptide segments or cassettes comprising the EPF protein sequence (BrAc-[EPF 78-101] 12, ClAc-[EPF 58-75]-[NHCH2CH2SH] 13, ClAc-[EPF 30-55]-[NHCH2CH2SH] 14, and Ac-[EPF 1-27]-[NHCH2CH2SH] 15) of EPF were synthesized in high yield and purity using Boc SPPS chemistry. In the stepwise sequential ligation strategy, reaction of peptides 12 and 13 was followed by conversion of the N-terminal chloroacetyl functional group to an iodoacetyl, thus activating the product peptide for further ligation with peptide 14. The process of ligation followed by iodoacetyl activation was repeated to yield an analogue of EPF (EPF psi(CH2S)(28-29,56-57,76-77)) 19 in 19% overall yield.

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Management systems standards (MSSs) have developed in an unprecedented manner in the last few years. These MSS cover a wide array of different disciplines, aims and activities of organisations. Also, organisations are populated with an enormous diversity of independent management systems (MSs). An integrated management system (IMS) tends to integrate some or all components of the business. Maximising their integration in one coherent and efficient MS is increasingly a strategic priority and constitutes an opportunity for businesses to be more competitive and consequently, promote its sustainable success. Those organisations that are quicker and more efficient in their integration and continuous improvement will have a competitive advantage in obtaining sustainable value in our global and competitive business world. Several scholars have proposed various theoretical approaches regarding the integration of management sub-systems, leading to the conclusion that there is no common practice for all organisations as they encompass different characteristics. One other author shows that several tangible and intangible gains for organisations, as well as to their internal and external stakeholders, are achieved with the integration of the individual standardised MSs. The purpose of this work was to conceive a model, Flexible, Integrator and Lean for IMSs, according to ISO 9001 for quality; ISO 14001 for environment and OHSAS 18001 for occupational health and safety (IMS–QES), that can be adapted and progressively assimilate other MSs, such as, SA 8000/ISO 26000 for social accountability, ISO 31000 for risk management and ISO/IEC 27001 for information security management, among others. The IMS–QES model was designed in the real environment of an industrial Portuguese small and medium enterprise, that over the years has been adopting, gradually, in whole or in part, individual MSSs. The developed model is based on a preliminary investigation conducted through a questionnaire. The strategy and research methods have taken into consideration the case study. Among the main findings of the survey we highlight: the creation of added value for the business through the elimination of several organisational wastes; the integrated management of the sustainability components; the elimination of conflicts between independent MS; dialogue with the main stakeholders and commitment to their ongoing satisfaction and increased contribution to the company’s competitiveness; and greater valorisation and motivation of employees as a result of the expansion of their skill base, actions and responsibilities, with their consequent empowerment. A set of key performance indicators (KPIs) constitute the support, in a perspective of business excellence, to the follow up of the organisation’s progress towards the vision and achievement of the defined objectives in the context of each component of the IMS model. The conceived model had many phases and the one presented in this work is the last required for the integration of quality, environment, safety and others individual standardised MSs. Globally, the investigation results, by themselves, justified and prioritised the conception of an IMS–QES model, to be implemented at the company where the investigation was conducted, but also a generic model of an IMS, which may be more flexible, integrator and lean as possible, potentiating the efficiency, added value both in the present and, fundamentally, for future.

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This study develops a theoretical model that explains the effectiveness of the balanced scorecard approach by means of a system dynamics and feedback learning perspective. Presumably, the balanced scorecard leads to a better understanding of context, allowing managers to externalize and improve their mental models. We present a set of hypotheses about the influence of the balanced scorecard approach on mental models and performance. A test based on a simulation experiment that uses a system dynamics model is performed. The experiment included three types of parameters: financial indicators; balanced scorecard indicators; and balanced scorecard indicators with the aid of a strategy map review. Two out of the three hypotheses were confirmed. It was concluded that a strategy map review positively influences mental model similarity, and mental model similarity positively influences performance.

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In this paper a realistic directional channel model that is an extension of the COST 273 channel model is presented. The model uses a cluster of scatterers and visibility region generation based strategy with increased realism, due to the introduction of terrain and clutter information. New approaches for path-loss prediction and line of sight modeling are considered, affecting the cluster path gain model implementation. The new model was implemented using terrain, clutter, street and user mobility information for the city of Lisbon, Portugal. Some of the model's outputs are presented, mainly path loss and small/large-scale fading statistics.