929 resultados para Brain Mathematical models
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The Artificial Neural Networks (ANNs) are mathematical models method capable of estimating non-linear response plans. The advantage of these models is to present different responses of the statistical models. Thus, the objective of this study was to develop and to test ANNs for estimating rainfall erosivity index (EI30) as a function of the geographical location for the state of Rio de Janeiro, Brazil and generating a thematic visualization map. The characteristics of latitude, longitude e altitude using ANNs were acceptable to estimating EI30 and allowing visualization of the space variability of EI30. Thus, ANN is a potential option for the estimate of climatic variables in substitution to the traditional methods of interpolation.
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It is presented a software developed with Delphi programming language to compute the reservoir's annual regulated active storage, based on the sequent-peak algorithm. Mathematical models used for that purpose generally require extended hydrological series. Usually, the analysis of those series is performed with spreadsheets or graphical representations. Based on that, it was developed a software for calculation of reservoir active capacity. An example calculation is shown by 30-years (from 1977 to 2009) monthly mean flow historical data, from Corrente River, located at São Francisco River Basin, Brazil. As an additional tool, an interface was developed to manage water resources, helping to manipulate data and to point out information that it would be of interest to the user. Moreover, with that interface irrigation districts where water consumption is higher can be analyzed as a function of specific seasonal water demands situations. From a practical application, it is possible to conclude that the program provides the calculation originally proposed. It was designed to keep information organized and retrievable at any time, and to show simulation on seasonal water demands throughout the year, contributing with the elements of study concerning reservoir projects. This program, with its functionality, is an important tool for decision making in the water resources management.
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The interaction between the soil and tillage tool can be examined using different parameters for the soil and the tool. Among the soil parameters are the shear stress, cohesion, internal friction angle of the soil and the pre-compression stress. The tool parameters are mainly the tool geometry and depth of operation. Regarding to the soils of Rio Grande do Sul there are hardly any studies and evaluations of the parameters that have importance in the use of mathematical models to predict tensile loads. The objective was to obtain parameters related to the soils of Rio Grande do Sul, which are used in soil-tool analysis, more specifically on mathematical models that allow the calculation of tractive effort for symmetric and narrow tools. Two of the main soils of Rio Grande do Sul, an Albaqualf and a Paleudult were studied. Equations that relate the cohesion, internal friction angle of the soil, adhesion, soil-tool friction angle and pre-compression stress as a function of water content in the soil were obtained, leading to important information for use of mathematical models for tractive effort calculation.
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Scarcity of long-term series of sediment-related variables has led watershed managers to apply mathematical models to simulate sediment fluxes. Due to the high efforts for installation and maintenance of sedimentological gauges, tracers have been pointed out as an alternative to validate soil redistribution modelling. In this study, the 137Cs technique was used to assess the WASA-SED model performance at the Benguê watershed (933 km²), in the Brazilian semiarid. Qualitatively, good agreement was found among the 137Cs technique and the WASA-SED model results. Nonetheless, quantitatively great differences, up to two orders of magnitude, were found between the two methods. Among the uncertainties inherent to the 137Cs technique, definition of the reference inventory seems to be a major source of imprecision. In addition, estimations of water and sediment fluxes with mathematical models usually also present high uncertainty, contributing to the quantitative differences of the soil redistribution estimates with the two methods.
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Quite often, in the construction of a pulp mill involves establishing the size of tanks which will accommodate the material from the various processes in which case estimating the right tank size a priori would be vital. Hence, simulation of the whole production process would be worthwhile. Therefore, there is need to develop mathematical models that would mimic the behavior of the output from the various production units of the pulp mill to work as simulators. Markov chain models, Autoregressive moving average (ARMA) model, Mean reversion models with ensemble interaction together with Markov regime switching models are proposed for that purpose.
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Dynaamisia simulointimalleja tarvitaan, jotta voidaan tarkastella järjestelmän käyttäytymistä ajan funktiona. Simulointimallilla voidaan simuloida järjestelmän lähtö erilaisilla herätteillä. Mallin avulla saadaan myös tarkempi käsitys järjestelmästä ja sen osa-alueista, koska simulointimallista voidaan tarkastella sellaisia asioita, jotka voivat olla oikeasta järjestelmästä vaikeasti mitattavia. Tässä työssä kehitetään LUT Energian hyötysuhdemittapaikan keskikokoista kalorimetriä approksimoiva dynaaminen lämmönsiirtomalli käyttäen Matlab® Simulink -ohjelmistoa. Kehitetyn lämmönsiirtomallin tarkkuutta arvioidaan todellisella järjestelmällä tehdyillä mittauksilla. Työssä käytetään karkeita approksimaatioita, jotka tulee korvata tarkemmilla matemaattisilla malleilla jatkokehitystä varten. Työssä kehitetty dynaaminen lämmönsiirtomalli approksimoi todellisen järjestelmän vastetta lämmitysvaiheessa keskimääräisenvirheen ±0,19 °C tarkkuudella.
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Programmed cell death is an important physiological cellular process that maintains homeostasis and protects multicellular organisms from diseases. Apoptosis is the principal mode of cell death, which eliminates unwanted cells and an enormous effort has been made to understand the molecular mechanisms of the signaling pathway and its regulatory systems. Irregular apoptosis often has life-threatening consequences to humans, including cancer, autoimmune diseases and degenerative diseases. In cancer for example, cell death is an attractive target to eradicate uncontrollably proliferating cells that have disregard pro-apoptotic signaling. Targeted therapeutic approaches are not as effective as once expected, since now we know that the cell death pathways are not sole entities in cells, but are highly associated with various cellular processes. Proteins that regulate apoptosis can also control non-apoptotic signaling pathways. For example, c-FLIP is a protein that can either inhibit or promote caspase-8 activation, which is required to induce apoptosis. Not only has c-FLIP opposing effects on initiating apoptosis, but it also regulates various pro-survival signaling pathways in the cell. It is well known that protein expression level is a determinant of how c-FLIP can regulate different signaling pathways, but other regulatory mechanisms potentially affecting the role of c-FLIP are less well understood. This work addresses novel insights into the mechanisms of c-FLIP post-translational modifications and their functional consequences. We have identified that phosphorylation is an important inception for subcellular localization of c-FLIP, thereby dictating which apoptotic and non-apoptotic signaling pathways c-FLIP could regulate to promote cell survival. Furthermore, we have constructed mathematical models to unite independent studies to establish more systematic c-FLIP signaling pathways to understand the dynamics of extrinsically-induced apoptosis.
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Lignocellulosic biomasses (e.g., wood and straws) are a potential renewable source for the production of a wide variety of chemicals that could be used to replace those currently produced by petrochemical industry. This would lead to lower greenhouse gas emissions and waste amounts, and to economical savings. There are many possible pathways available for the manufacturing of chemicals from lignocellulosic biomasses. One option is to hydrolyze the cellulose and hemicelluloses of these biomasses into monosaccharides using concentrated sulfuric acid as catalyst. This process is an efficient method for producing monosaccharides which are valuable platforn chemicals. Also other valuable products are formed in the hydrolysis. Unfortunately, the concentrated acid hydrolysis has been deemed unfeasible mainly due to high chemical consumption resulting from the need to remove sulfuric acid from the obtained hydrolysates prior to the downstream processing of the monosaccharides. Traditionally, this has been done by neutralization with lime. This, however, results in high chemical consumption. In addition, the by-products formed in the hydrolysis are not removed and may, thus, hinder the monosaccharide processing. In order to improve the feasibility of the concentrated acid hydrolysis, the chemical consumption should be decreased by recycling of sulfuric acid without neutralization. Furthermore, the monosaccharides and the other products formed in the hydrolysis should be recovered selectively for efficient downstream processing. The selective recovery of the hydrolysis by-products would have additional economical benefits on the process due to their high value. In this work, the use of chromatographic fractionation for the recycling of sulfuric acid and the selective recovery of the main components from the hydrolysates formed in the concentrated acid hydrolysis was investigated. Chromatographic fractionation based on the electrolyte exclusion with gel type strong acid cation exchange resins in acid (H+) form as a stationary phase was studied. A systematic experimental and model-based study regarding the separation task at hand was conducted. The phenomena affecting the separation were determined and their effects elucidated. Mathematical models that take accurately into account these phenomena were derived and used in the simulation of the fractionation process. The main components of the concentrated acid hydrolysates (sulfuric acid, monosaccharides, and acetic acid) were included into this model. Performance of the fractionation process was investigated experimentally and by simulations. Use of different process options was also studied. Sulfuric acid was found to have a significant co-operative effect on the sorption of the other components. This brings about interesting and beneficial effects in the column operations. It is especially beneficial for the separation of sulfuric acid and the monosaccharides. Two different approaches for the modelling of the sorption equilibria were investigated in this work: a simple empirical approach and a thermodynamically consistent approach (the Adsorbed Solution theory). Accurate modelling of the phenomena observed in this work was found to be possible using the simple empirical models. The use of the Adsorbed Solution theory is complicated by the nature of the theory and the complexity of the studied system. In addition to the sorption models, a dynamic column model that takes into account the volume changes of the gel type resins as changing resin bed porosity was also derived. Using the chromatography, all the main components of the hydrolysates can be recovered selectively, and the sulfuric acid consumption of the hydrolysis process can be lowered considerably. Investigation of the performance of the chromatographic fractionation showed that the highest separation efficiency in this separation task is obtained with a gel type resin with a high crosslinking degree (8 wt. %); especially when the hydrolysates contain high amounts of acetic acid. In addition, the concentrated acid hydrolysis should be done with as low sulfuric acid concentration as possible to obtain good separation performance. The column loading and flow rate also have large effects on the performance. In this work, it was demonstrated that when recycling of the fractions obtained in the chromatographic fractionation are recycled to preceding unit operations these unit operations should included in the performance evaluation of the fractionation. When this was done, the separation performance and the feasibility of the concentrated acid hydrolysis process were found to improve considerably. Use of multi-column chromatographic fractionation processes, the Japan Organo process and the Multi-Column Recycling Chromatography process, was also investigated. In the studied case, neither of these processes could compete with the single-column batch process in the productivity. However, due to internal recycling steps, the Multi-Column Recycling Chromatography was found to be superior to the batch process when the product yield and the eluent consumption were taken into account.
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This work was carried out with the objective of evaluating the growth and development of honey weed (Leonurus sibiricus) based on days or thermal units (growing degree days). Thus, two independent trials were developed to quantify the phenological development and total dry mass accumulation in increasing or decreasing photoperiod conditions. Considering only one growing season, honey weed phenological development was perfectly fit to day scale or growing degree days, but with no equivalence between seasons, with the plants developing faster at increasing photoperiods, and flowering 100 days after seeding. Even day-time scale or thermal units were not able to estimate general honey weed phenology during the different seasons of the year. In any growing condition, honey weed plants were able to accumulate a total dry mass of over 50 g per plant. Dry mass accumulation was adequately fit to the growing degree days, with highlights to a base temperature of 10 ºC. Therefore, a higher environmental influence on species phenology and a lower environmental influence on growth (dry mass) were observed, showing thereby that other variables, such as the photoperiod, may potentially complement the mathematical models.
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Availability of basic information on weed biology is an essential tool for designing integrated management programs for agricultural systems. Thus, this study was carried out in order to calculate the base temperature (Tb) of southern sandbur (Cenchrus echinatus), as well as fit the initial growth and development of the species to accumulated thermal units (growing degree days - GDD). For that purpose, experimental populations were sown six times in summer/autumn conditions (decreasing photoperiod) and six times in winter/spring condition (increasing photoperiod). Southern sandbur phenological evaluations were carried out, on alternate days, and total dry matter was measured when plants reached the flowering stage. All the growth and development fits were performed based on thermal units by assessing five base temperatures, as well as the absence of it. Southern sandbur development was best fit with Tb = 12 ºC, with equation y = 0,0993x, where y is the scale of phenological stage and x is the GDD. On average, flowering was reached at 518 GDD. Southern sandbur phenology may be predicted by using mathematical models based on accumulated thermal units, adopting Tb = 12 ºC. However, other environmental variables may also interfere with species development, particularly photoperiod.
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This work was carried out with the objective of evaluating growth and development of sourgrass (Digitaris insularis) based on days or thermal units (growing degree days - GDD). Two independent trials were developed aiming to quantify the species' phenological development and total dry matter accumulation in increasing or decreasing photoperiod conditions. Plants were grown in 4 L plastic pots, filled with commercial substrate, adequately fertilized. In each trial, nine growth evaluations were carried out, with three replicates. Phenological development of sourgrass was correctly fit to time scale in days or GDD, through linear equation of first degree. Sourgrass has slow initial growth, followed by exponential dry matter accumulation, in increasing photoperiod condition. Maximum total dry matter was 75 and 6 g per plant for increasing and decreasing photoperiod conditions, respectively. Thus, phenological development of sourgrass may be predicted by mathematical models based on days or GDD; however, it should be noted that other environmental variables interfere on the species' growth (mass accumulation), especially photoperiod.
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This work was carried out with the objective of elaborating mathematical models to predict growth and development of purple nutsedge (Cyperus rotundus) based on days or accumulated thermal units (growing degree days). Thus, two independent trials were developed, the first with a decreasing photoperiod (March to July) and the second with an increasing photoperiod (August to November). In each trial, ten assessments of plant growth and development were performed, quantifying total dry matter and the species phenology. After that, phenology was fit to first degree equations, considering individual trials or their grouping. In the same way, the total dry matter was fit to logistic-type models. In all regressions four temporal scales possibilities were assessed for the x axis: accumulated days or growing degree days (GDD) with base temperatures (Tb) of 10, 12 and 15 oC. For both photoperiod conditions, growth and development of purple nutsedge were adequately fit to prediction mathematical models based on accumulated thermal units, highlighting Tb = 12 oC. Considering GDD calculated with Tb = 12 oC, purple nutsedge phenology may be predicted by y = 0.113x, while species growth may be predicted by y = 37.678/(1+(x/509.353)-7.047).
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The objective of this master’s thesis was to design and simulate a wind powered hydraulic heating system that can operate independently in remote places where the use of electricity is not possible. Components for the system were to be selected in such a way that the conditions for manufacture, use and economic viability are the as good as possible. Savonius rotor was chosen for wind turbine, due to its low cut in speed and robust design. Savonius rotor produces kinetic energy in wide wind speed range and it can withstand high wind gusts. Radial piston pump was chosen for the flow source of the hydraulic heater. Pump type was selected due to its characteristics in low rotation speeds and high efficiency. Volume flow from the pump is passed through the throttle orifice. Pressure drop over the orifice causes the hydraulic oil to heat up and, thus, creating thermal energy. Thermal energy in the oil is led to radiator where it conducts heat to the environment. The hydraulic heating system was simulated. For this purpose a mathematical models of chosen components were created. In simulation wind data gathered by Finnish meteorological institute for 167 hours was used as input. The highest produced power was achieved by changing the orifice diameter so that the rotor tip speed ratio follows the power curve. This is not possible to achieve without using electricity. Thus, for the orifice diameter only one, the optimal value was defined. Results from the simulation were compared with investment calculations. Different parameters effecting the investment profitability were altered in sensitivity analyses in order to define the points of investment profitability. Investment was found to be profitable only with high average wind speeds.
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Almost every problem of design, planning and management in the technical and organizational systems has several conflicting goals or interests. Nowadays, multicriteria decision models represent a rapidly developing area of operation research. While solving practical optimization problems, it is necessary to take into account various kinds of uncertainty due to lack of data, inadequacy of mathematical models to real-time processes, calculation errors, etc. In practice, this uncertainty usually leads to undesirable outcomes where the solutions are very sensitive to any changes in the input parameters. An example is the investment managing. Stability analysis of multicriteria discrete optimization problems investigates how the found solutions behave in response to changes in the initial data (input parameters). This thesis is devoted to the stability analysis in the problem of selecting investment project portfolios, which are optimized by considering different types of risk and efficiency of the investment projects. The stability analysis is carried out in two approaches: qualitative and quantitative. The qualitative approach describes the behavior of solutions in conditions with small perturbations in the initial data. The stability of solutions is defined in terms of existence a neighborhood in the initial data space. Any perturbed problem from this neighborhood has stability with respect to the set of efficient solutions of the initial problem. The other approach in the stability analysis studies quantitative measures such as stability radius. This approach gives information about the limits of perturbations in the input parameters, which do not lead to changes in the set of efficient solutions. In present thesis several results were obtained including attainable bounds for the stability radii of Pareto optimal and lexicographically optimal portfolios of the investment problem with Savage's, Wald's criteria and criteria of extreme optimism. In addition, special classes of the problem when the stability radii are expressed by the formulae were indicated. Investigations were completed using different combinations of Chebyshev's, Manhattan and Hölder's metrics, which allowed monitoring input parameters perturbations differently.
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This paper evaluated the influence of temperature and concentration of the sucrose syrup on the pre-osmotic dehydration of peaches. Physical (colour and texture) and chemical variables (soluble solid content; total sugar, reducing and non-reducing sugar contents; and titratable acidity) were investigated, as well as the osmotic dehydration parameters (loss of weight and water; solids incorporation). An experimental central composite design was employed varying the temperature (from 30 to 50 ºC) and concentration (from 45 to 65 ºBrix) and maintaining the syrup to fruit ratio (4:1), process time (4 hours), and format (slices). The degree of acceptance was used in the sensory analysis evaluating the following characteristics: appearance, taste, texture, colour, and overall quality using a hedonic scale. The results were modelled using the Statistica program (v. 6.0) and the Response Surface Methodology. The mathematical models of the following dimensionless variations yielded significant (p < 0.05) and predictive results: soluble solids content, total and non-reducing sugar contents, titratable acidity, colour parameter L*, and water loss. The models of the attributes colour and appearance yielded significant (p < 0.10) but not predictive results. Temperature was the prevalent effect in the models. The process conditions in the range from 50 to 54.1 ºC and from 45 to 65 ºBrix led to greater water losses and better sensory performances.