969 resultados para 2-perfect Extended M-cycle Systems


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Globalization as progress of economic development has increased population socioeconomical vulnerability when unequal wealth distribution within economic development process constitutes the main rule, with widening the gap between rich and poors by environmental pricing. Econological vulnerability is therefore increasing too, as dangerous substance and techniques should produce polluted effluents and industrial or climatic risk increasing (Woloszyn, Quenault, Faburel, 2012). To illustrate and model this process, we propose to introduce an analogical induction-model to describe both vulnerability situations and associated resilience procedures. At this aim, we first develop a well-known late 80?s model of socio-economic crack-up, known as 'Silent Weapons for Quiet Wars', which presents economics as a social extension of natural energy systems. This last, also named 'E-model', is constituted by three passive components, potential energy, kinetic energy, and energy dissipation, thus allowing economical data to be treated as a thermodynamical system. To extend this model to social and ecological sustainability pillars, we propose to built an extended E(Economic)-S(Social)-O(Organic) model, based on the three previous components, as an open model considering feedbacks as evolution sources. An applicative illustration of this model will then be described, through this summer's american severe drought event analysis

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Globalization as progress of economic development has increased population socioeconomical vulnerability when unequal wealth distribution within economic development process constitutes the main rule, with widening the gap between rich and poors by environmental pricing. Econological vulnerability is therefore increasing too, as dangerous substance and techniques should produce polluted effluents and industrial or climatic risk increasing (Woloszyn, Quenault, Faburel, 2012). To illustrate and model this process, we propose to introduce an analogical induction-model to describe both vulnerability situations and associated resilience procedures. At this aim, we first develop a well-known late 80?s model of socio-economic crack-up, known as 'Silent Weapons for Quiet Wars', which presents economics as a social extension of natural energy systems. This last, also named 'E-model', is constituted by three passive components, potential energy, kinetic energy, and energy dissipation, thus allowing economical data to be treated as a thermodynamical system. To extend this model to social and ecological sustainability pillars, we propose to built an extended E(Economic)-S(Social)-O(Organic) model, based on the three previous components, as an open model considering feedbacks as evolution sources. An applicative illustration of this model will then be described, through this summer's american severe drought event analysis

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This paper describes new approaches to improve the local and global approximation (matching) and modeling capability of Takagi–Sugeno (T-S) fuzzy model. The main aim is obtaining high function approximation accuracy and fast convergence. The main problem encountered is that T-S identification method cannot be applied when the membership functions are overlapped by pairs. This restricts the application of the T-S method because this type of membership function has been widely used during the last 2 decades in the stability, controller design of fuzzy systems and is popular in industrial control applications. The approach developed here can be considered as a generalized version of T-S identification method with optimized performance in approximating nonlinear functions. We propose a noniterative method through weighting of parameters approach and an iterative algorithm by applying the extended Kalman filter, based on the same idea of parameters’ weighting. We show that the Kalman filter is an effective tool in the identification of T-S fuzzy model. A fuzzy controller based linear quadratic regulator is proposed in order to show the effectiveness of the estimation method developed here in control applications. An illustrative example of an inverted pendulum is chosen to evaluate the robustness and remarkable performance of the proposed method locally and globally in comparison with the original T-S model. Simulation results indicate the potential, simplicity, and generality of the algorithm. An illustrative example is chosen to evaluate the robustness. In this paper, we prove that these algorithms converge very fast, thereby making them very practical to use.

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Forward error correction (FEC) plays a vital role in coherent optical systems employing multi-level modulation. However, much of coding theory assumes that additive white Gaussian noise (AWGN) is dominant, whereas coherent optical systems have significant phase noise (PN) in addition to AWGN. This changes the error statistics and impacts FEC performance. In this paper, we propose a novel semianalytical method for dimensioning binary Bose-Chaudhuri-Hocquenghem (BCH) codes for systems with PN. Our method involves extracting statistics from pre-FEC bit error rate (BER) simulations. We use these statistics to parameterize a bivariate binomial model that describes the distribution of bit errors. In this way, we relate pre-FEC statistics to post-FEC BER and BCH codes. Our method is applicable to pre-FEC BER around 10-3 and any post-FEC BER. Using numerical simulations, we evaluate the accuracy of our approach for a target post-FEC BER of 10-5. Codes dimensioned with our bivariate binomial model meet the target within 0.2-dB signal-to-noise ratio.

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With the continued miniaturization and increasing performance of electronic devices, new technical challenges have arisen. One such issue is delamination occurring at critical interfaces inside the device. This major reliability issue can occur during the manufacturing process or during normal use of the device. Proper evaluation of the adhesion strength of critical interfaces early in the product development cycle can help reduce reliability issues and time-to-market of the product. However, conventional adhesion strength testing is inherently limited in the face of package miniaturization, which brings about further technical challenges to quantify design integrity and reliability. Although there are many different interfaces in today's advanced electronic packages, they can be generalized into two main categories: 1) rigid to rigid connections with a thin flexible polymeric layer in between, or 2) a thin film membrane on a rigid structure. Knowing that every technique has its own advantages and disadvantages, multiple testing methods must be enhanced and developed to be able to accommodate all the interfaces encountered for emerging electronic packaging technologies. For evaluating the adhesion strength of high adhesion strength interfaces in thin multilayer structures a novel adhesion test configuration called “single cantilever adhesion test (SCAT)” is proposed and implemented for an epoxy molding compound (EMC) and photo solder resist (PSR) interface. The test method is then shown to be capable of comparing and selecting the stronger of two potential EMC/PSR material sets. Additionally, a theoretical approach for establishing the applicable testing domain for a four-point bending test method was presented. For evaluating polymeric films on rigid substrates, major testing challenges are encountered for reducing testing scatter and for factoring in the potentially degrading effect of environmental conditioning on the material properties of the film. An advanced blister test with predefined area test method was developed that considers an elasto-plastic analytical solution and implemented for a conformal coating used to prevent tin whisker growth. The advanced blister testing with predefined area test method was then extended by employing a numerical method for evaluating the adhesion strength when the polymer’s film properties are unknown.

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Background: An evaluation of patients' preferences is necessary to understand the demand for different insulin delivery systems. The aim of this study was to investigate the association between socioeconomic status (SES) and patients' preferences and willingness to pay (WTP) for various attributes of insulin administration for diabetes management. Methods: We conducted a discrete choice experiment (DCE) to determine patients' preferences and their WTP for hypothetical insulin treatments. Both self-reported annual household income and education completed were used to explore differences in treatment preferences and WTP for different attributes of treatment across different levels of SES. Results: The DCE questionnaire was successfully completed by 274 patients. Overall, glucose control was the most valued attribute by all socioeconomic groups, while route of insulin delivery was not as important. Patients with higher incomes were willing to pay significantly more for better glucose control and to avoid adverse events compared to lower income groups. In addition, they were willing to pay more for an oral short-acting insulin ($Can 71.65 [95% confidence interval, $40.68, $102.62]) compared to the low income group ($Can 9.85 [95% confidence interval, 14.86, 34.56; P < 0.01]). Conversely, there were no differences in preferences when the sample was stratified by level of education. Conclusions: This study revealed that preferences and WTP for insulin therapy are influenced by income but not by level of education. Specifically, the higher the income, the greater desire for an oral insulin delivery system, whereas an inhaled route becomes less important for patients.

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The crystal structure and the local atomic order of a series of nanocrystalline ZrO(2)-CaO solid solutions with varying CaO content were studied by synchrotron radiation X-ray powder diffraction and extended X-ray absorption fine structure (EXAFS) spectroscopy. These samples were synthesized by a pH-controlled nitrate-glycine gel-combustion process. For CaO contents up to 8 mol%, the t' form of the tetragonal phase (c/a > 1) was identified, whereas for 10 and 12 mol% CaO, the t '' form (c/a=1; oxygen anions displaced from their ideal positions in the cubic phase) was detected. Finally, the cubic phase was observed for solid solutions with CaO content of 14 mol% CaO or higher. The t'/t '' and t ''/cubic compositional boundaries were determined to be at 9 (1) and 13 (1) mol% CaO, respectively. The EXAFS study demonstrated that this transition is related to a tetragonal-to-cubic symmetry change of the first oxygen coordination shell around the Zr atoms.

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We adopt the Dirac model for graphene and calculate the Casimir interaction energy between a plane suspended graphene sample and a parallel plane perfect conductor. This is done in two ways. First, we use the quantum-field-theory approach and evaluate the leading-order diagram in a theory with 2+1-dimensional fermions interacting with 3+1-dimensional photons. Next, we consider an effective theory for the electromagnetic field with matching conditions induced by quantum quasiparticles in graphene. The first approach turns out to be the leading order in the coupling constant of the second one. The Casimir interaction for this system appears to be rather weak. It exhibits a strong dependence on the mass of the quasiparticles in graphene.

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The influence of interlayer coupling on the formation of the quantized Hall phase at the filling factor nu=2 was studied in multilayer GaAs/AlGaAs heterostructures. The disorder broadened Gaussian photoluminescence line due to localized electrons was found in the quantized Hall phase of the isolated multi-quanturn-well structure. On the other hand, the quantized Hall phase of weakly coupled multilayers emitted an unexpected asymmetrical line similar to that observed in metallic electron systems. We demonstrated that the observed asymmetry is caused by the partial population of extended electron states formed in the insulating quantized Hall phase due to spin-assisted interlayer percolation. A sharp decrease in the single-particle scattering time associated with these extended states was observed for the filling factor nu=2. (C) 2008 American Institute of Physics. [DOI: 10.1063/1.2978194]

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Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

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Agricultural management practices that promote net carbon (C) accumulation in the soil have been considered as an important potential mitigation option to combat global warming. The change in the sugarcane harvesting system, to one which incorporates C into the soil from crop residues, is the focus of this work. The main objective was to assess and discuss the changes in soil organic C stocks caused by the conversion of burnt to unburnt sugarcane harvesting systems in Brazil, when considering the main soils and climates associated with this crop. For this purpose, a dataset was obtained from a literature review of soils under sugarcane in Brazil. Although not necessarily from experimental studies, only paired comparisons were examined, and for each site the dominant soil type, topography and climate were similar. The results show a mean annual C accumulation rate of 1.5 Mg ha-1 year-1 for the surface to 30-cm depth (0.73 and 2.04 Mg ha-1 year-1 for sandy and clay soils, respectively) caused by the conversion from a burnt to an unburnt sugarcane harvesting system. The findings suggest that soil should be included in future studies related to life cycle assessment and C footprint of Brazilian sugarcane ethanol.

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Outgassing of carbon dioxide (CO(2)) from rivers and streams to the atmosphere is a major loss term in the coupled terrestrial-aquatic carbon cycle of major low-gradient river systems (the term ""river system"" encompasses the rivers and streams of all sizes that compose the drainage network in a river basin). However, the magnitude and controls on this important carbon flux are not well quantified. We measured carbon dioxide flux rates (F(CO2)), gas transfer velocity (k), and partial pressures (p(CO2)) in rivers and streams of the Amazon and Mekong river systems in South America and Southeast Asia, respectively. F(CO2) and k values were significantly higher in small rivers and streams (channels <100 m wide) than in large rivers (channels >100 m wide). Small rivers and streams also had substantially higher variability in k values than large rivers. Observed F(CO2) and k values suggest that previous estimates of basinwide CO(2) evasion from tropical rivers and wetlands have been conservative and are likely to be revised upward substantially in the future. Data from the present study combined with data compiled from the literature collectively suggest that the physical control of gas exchange velocities and fluxes in low-gradient river systems makes a transition from the dominance of wind control at the largest spatial scales (in estuaries and river mainstems) toward increasing importance of water current velocity and depth at progressively smaller channel dimensions upstream. These results highlight the importance of incorporating scale-appropriate k values into basinwide models of whole ecosystem carbon balance.

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Biofuels are both a promising solution to global warming mitigation and a potential contributor to the problem. Several life cycle assessments of bioethanol have been conducted to address these questions. We performed a synthesis of the available data on Brazilian ethanol production focusing on greenhouse gas (GHG) emissions and carbon (C) sinks in the agricultural and industrial phases. Emissions of carbon dioxide (CO(2)) from fossil fuels, methane (CH(4)) and nitrous oxide (N(2)O) from sources commonly included in C footprints, such as fossil fuel usage, biomass burning, nitrogen fertilizer application, liming and litter decomposition were accounted for. In addition, black carbon (BC) emissions from burning biomass and soil C sequestration were included in the balance. Most of the annual emissions per hectare are in the agricultural phase, both in the burned system (2209 out of a total of 2398 kg C(eq)), and in the unburned system (559 out of 748 kg C(eq)). Although nitrogen fertilizer emissions are large, 111 kg C(eq) ha-1 yr-1, the largest single source of emissions is biomass burning in the manual harvest system, with a large amount of both GHG (196 kg C(eq) ha-1 yr-1). and BC (1536 kg C(eq) ha-1 yr-1). Besides avoiding emissions from biomass burning, harvesting sugarcane mechanically without burning tends to increase soil C stocks, providing a C sink of 1500 kg C ha-1 yr-1 in the 30 cm layer. The data show a C output: input ratio of 1.4 for ethanol produced under the conventionally burned and manual harvest compared with 6.5 for the mechanized harvest without burning, signifying the importance of conservation agricultural systems in bioethanol feedstock production.

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This study investigated the energy system contributions of rowers in three different conditions: rowing on an ergometer without and with the slide and rowing in the water. For this purpose, eight rowers were submitted to 2,000 m race simulations in each of the situations defined above. The fractions of the aerobic (W(AER)), anaerobic alactic (W(PCR)) and anaerobic lactic (W([La-])) systems were calculated based on the oxygen uptake, the fast component of excess post-exercise oxygen uptake and changes in net blood lactate, respectively. In the water, the metabolic work was significantly higher [(851 (82) kJ] than during both ergometer [674 (60) kJ] and ergometer with slide [663 (65) kJ] (P <= 0.05). The time in the water [515 (11) s] was higher (P < 0.001) than in the ergometers with [398 (10) s] and without the slide [402 (15) s], resulting in no difference when relative energy expenditure was considered: in the water [99 (9) kJ min(-1)], ergometer without the slide [99.6 (9) kJ min(-1)] and ergometer with the slide [100.2 (9.6) kJ min(-1)]. The respective contributions of the WAER, WPCR and W[La-] systems were water = 87 (2), 7 (2) and 6 (2)%, ergometer = 84 (2), 7 (2) and 9 (2)%, and ergometer with the slide = 84 (2), 7 (2) and 9 (1)%. (V) over dotO(2), HR and lactate were not different among conditions. These results seem to indicate that the ergometer braking system simulates conditions of a bigger and faster boat and not a single scull. Probably, a 2,500 m test should be used to properly simulate in the water single-scull race.

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Research of advanced technologies for energy generation contemplates a series of alternatives that are introduced both in the investigation of new energy sources and in the improvement and/or development of new components and systems. Even though significant reductions are observed in the amount of emissions, the proposed alternatives require the use of exhaust gases cleaning systems. The results of environmental analyses based on two configurations proposed for urban waste incineration are presented in this paper; the annexation of integer (Boolean) variables to the environomic model makes it possible to define the best gas cleaning routes based on exergetic cost minimisation criteria. In this first part, the results for steam cogeneration system analysis associated with the incineration of municipal solid wastes (MSW) is presented. (c) 2007 Elsevier Ltd. All rights reserved.