965 resultados para Dynamic state


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Solid waste generation is a natural consequence of human activity and is increasing along with population growth, urbanization and industrialization. Improper disposal of the huge amount of solid waste seriously affects the environment and contributes to climate change by the release of greenhouse gases. Practicing anaerobic digestion (AD) for the organic fraction of municipal solid waste (OFMSW) can reduce emissions to environment and thereby alleviate the environmental problems together with production of biogas, an energy source, and digestate, a soil amendment. The amenability of substrate for biogasification varies from substrate to substrate and different environmental and operating conditions such as pH, temperature, type and quality of substrate, mixing, retention time etc. Therefore, the purpose of this research work is to develop feasible semi-dry anaerobic digestion process for the treatment of OFMSW from Kerala, India for potential energy recovery and sustainable waste management. This study was carried out in three phases in order to reach the research purpose. In the first phase, batch study of anaerobic digestion of OFMSW was carried out for 100 days at 32°C (mesophilic digestion) for varying substrate concentrations. The aim of this study was to obtain the optimal conditions for biogas production using response surface methodology (RSM). The parameters studied were initial pH, substrate concentration and total organic carbon (TOC). The experimental results showed that the linear model terms of initial pH and substrate concentration and the quadratic model terms of the substrate concentration and TOC had significant individual effect (p < 0.05) on biogas yield. However, there was no interactive effect between these variables (p > 0.05). The optimum conditions for maximizing the biogas yield were a substrate concentration of 99 g/l, an initial pH of 6.5 and TOC of 20.32 g/l. AD of OFMSW with optimized substrate concentration of 99 g/l [Total Solid (TS)-10.5%] is a semi-dry digestion system .Under the optimized condition, the maximum biogas yield was 53.4 L/kg VS (volatile solid).. In the second phase, semi-dry anaerobic digestion of organic solid wastes was conducted for 45 days in a lab-scale batch experiment for substrate concentration of 100 g/l (TS-11.2%) for investigating the start-up performances under thermophilic condition (50°C). The performance of the reactor was evaluated by measuring the daily biogas production and calculating the degradation of total solids and the total volatile solids. The biogas yield at the end of the digestion was 52.9 L/kg VS for the substrate concentration of 100 g/l. About 66.7% of volatile solid degradation was obtained during the digestion. A first order model based on the availability of substrate as the limiting factor was used to perform the kinetic studies of batch anaerobic digestion system. The value of reaction rate constant, k, obtained was 0.0249 day-1. A laboratory bench scale reactor with a capacity of 36.8 litres was designed and fabricated to carry out the continuous anaerobic digestion of OFMSW in the third phase. The purpose of this study was to evaluate the performance of the digester at total solid concentration of 12% (semi-dry) under mesophlic condition (32°C). The digester was operated with different organic loading rates (OLRs) and constant retention time. The performance of the reactor was evaluated using parameters such as pH, volatile fatty acid (VFA), alkalinity, chemical oxygen demand (COD), TOC and ammonia-N as well as biogas yield. During the reactor’s start-up period, the process is stable and there is no inhibition occurred and the average biogas production was 14.7 L/day. The reactor was fed in continuous mode with different OLRs (3.1,4.2 and 5.65 kg VS/m3/d) at constant retention time of 30 days. The highest volatile solid degradation of 65.9%, with specific biogas production of 368 L/kg VS fed was achieved with OLR of 3.1 kg VS/m3/d. Modelling and simulation of anaerobic digestion of OFMSW in continuous operation is done using adapted Anaerobic Digestion Model No 1 (ADM1).The proposed model, which has 34 dynamic state variables, considers both biochemical and physicochemical processes and contains several inhibition factors including three gas components. The number of processes considered is 28. The model is implemented in Matlab® version 7.11.0.584(R2010b). The model based on adapted ADM1 was tested to simulate the behaviour of a bioreactor for the mesophilic anaerobic digestion of OFMSW at OLR of 3.1 kg VS/m3/d. ADM1 showed acceptable simulating results.

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This study aims to evaluate and correlate the vascular, sensory and motor components related to the plantar surface in individuals with diabetic peripheral neuropathy. 68 patients were categorized into two groups: 28 in the neuropathic group and 40 in the control group. In each patient, we assessed: circulation and peripheral perfusion of the lower limbs; somatosensory sensitivity; ankle muscle strength; and pressure on the plantar surface in static, dynamic and gait states. We used the Mann-Whitney test and analysis of variance (ANOVA and MANOVA) for comparison between groups, and performed Pearson and Spearman linear correlations amongst the variables (P < 0.05). The somatosensory sensitivity, peripheral circulation and ankle muscle strength were reduced in the neuropathic group. In full peak plantar pressures, no differences were seen between groups, but differences did appear when the foot surface was divided into regions (forefoot, midfoot and hindfoot). In the static condition, the plantar surface area was greater in the neuropathic group. In the dynamic state, peak pressures in the neuropathic group, were higher in the forefoot and lower in the hindfoot, as well as lower in the hindfoot during gait. There were positive or negative correlations between the sensitivity deficit, dorsal ankle flexor strength, plantar surface area, and peak pressure by plantar region. The sensitivity deficit contributed to the increased plantar surface area.

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Attractive business cases in various application fields contribute to the sustained long-term interest in indoor localization and tracking by the research community. Location tracking is generally treated as a dynamic state estimation problem, consisting of two steps: (i) location estimation through measurement, and (ii) location prediction. For the estimation step, one of the most efficient and low-cost solutions is Received Signal Strength (RSS)-based ranging. However, various challenges - unrealistic propagation model, non-line of sight (NLOS), and multipath propagation - are yet to be addressed. Particle filters are a popular choice for dealing with the inherent non-linearities in both location measurements and motion dynamics. While such filters have been successfully applied to accurate, time-based ranging measurements, dealing with the more error-prone RSS based ranging is still challenging. In this work, we address the above issues with a novel, weighted likelihood, bootstrap particle filter for tracking via RSS-based ranging. Our filter weights the individual likelihoods from different anchor nodes exponentially, according to the ranging estimation. We also employ an improved propagation model for more accurate RSS-based ranging, which we suggested in recent work. We implemented and tested our algorithm in a passive localization system with IEEE 802.15.4 signals, showing that our proposed solution largely outperforms a traditional bootstrap particle filter.

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The influence of thermally induced changes in the lipid core structure on the oxidative resistance of discrete, homogeneous low density lipoprotein (LDL) subspecies (d, 1.0297-1.0327 and 1.0327-1.0358 g/ml) has been evaluated. The thermotropic transition of the LDL lipid core at temperatures between 15 degrees C and 37 degrees C, determined by differential scanning calorimetry, exerted significant effects on the kinetics of copper-mediated LDL oxidation expressed in terms of intrinsic antioxidant efficiency (lag time) and diene production rate. Thus, the temperature coefficients of oxidative resistance and maximum oxidation rate showed break points at the core transition temperature. Temperature-induced changes in copper binding were excluded as the molecular basis of such effects, as the saturation of LDL with copper was identical below and above the core transition. At temperatures below the transition, the elevation in lag time indicated a greater resistance to oxidation, reflecting a higher degree of antioxidant protection. This effect can be explained by higher motional constraints and local antioxidant concentrations, the latter resulting from the freezing out of antioxidants from crystalline domains of cholesteryl esters and triglycerides. Below the transition temperature, the conjugated diene production rate was decreased, a finding that correlated positively with the average size of the cooperative units of neutral lipids estimated from the calorimetric transition width. The reduced accessibility and structural hindrance in the cluster organization of the core lipids therefore inhibits peroxidation. Our findings provide evidence for a distinct effect of the dynamic state of the core lipids on the oxidative susceptibility of LDL and are therefore relevant to the atherogenicity of these cholesterol-rich particles.

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The exchange of proteins and lipids between the trans-Golgi network (TGN) and the endosomal system requires multiple cellular machines, whose activities are coordinated in space and time to generate pleomorphic, tubulo-vesicular carriers that deliver their content to their target compartments. These machines and their associated protein networks are recruited and/or activated on specific membrane domains where they select proteins and lipids into carriers, contribute to deform/elongate and partition membrane domains using the mechanical forces generated by actin polymerization or movement along microtubules. The coordinated action of these protein networks contributes to regulate the dynamic state of multiple receptors recycling between the cell surface, endosomes and the TGN, to maintain cell homeostasis as exemplified by the biogenesis of lysosomes and related organelles, and to establish/maintain cell polarity. The dynamic assembly and disassembly of these protein networks mediating the exchange of membrane domains between the TGN and endosomes regulates cell-cell signalling and thus the development of multi-cellular organisms. Somatic mutations in single network components lead to changes in transport dynamics that may contribute to pathological modifications underlying several human diseases such as mental retardation.

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On the basis of human evolution and the population increase was necessary, the emergence of new sources of energy, the development of new products and technologies. One such product, object of the industry revolution and of great importance to the development of humanity is the oil, a substance composed primarily of hydrocarbons which give rise to several other products as fuels, lubricants, polymers, solvents, cooking gas, asphalt for roads, fertilizers, medicines, paints, among other. However, mishandling this product may cause leaks and spills that generate huge damages to the environment and the economy. Soon, with the purpose of contributing to decrease is problematic, in this master's work was carried out an intensive search of the possible potential of the fibers of Ceiba pentandra (L.) "Kapok" and Calotropis Procera as bioadsorbents of petroleum in water. The choice of these fibers is due to surface properties such as oleophylics and hydrophobic, their buoyancy and yet, being biodegradable natural polymers derived from the Brazilian Northeast. This research was used experimental planning with response surface methodology (RSM) with the software Design Expert. The results were statistically efficient, obtaining a R2= 0.9995 for Calotropis Procera and a R2= 0.9993 for Kapok. And that, both fibers showed adsorption efficiency, removing more than 80% petroleum in water static and dynamic state.

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The main inputs to the hippocampus arise from the entorhinal cortex (EC) and form a loop involving the dentate gyrus, CA3 and CA1 hippocampal subfields and then back to EC. Since the discovery that the hippocampus is involved in memory formation in the 50's, this region and its circuitry have been extensively studied. Beyond memory, the hippocampus has also been found to play an important role in spatial navigation. In rats and mice, place cells show a close relation between firing rate and the animal position in a restricted area of the environment, the so-called place field. The firing of place cells peaks at the center of the place field and decreases when the animal moves away from it, suggesting the existence of a rate code for space. Nevertheless, many have described the emergence of hippocampal network oscillations of multiple frequencies depending on behavioral state, which are believed to be important for temporal coding. In particular, theta oscillations (5-12 Hz) exhibit a spatio-temporal relation with place cells known as phase precession, in which place cells consistently change the theta phase of spiking as the animal traverses the place field. Moreover, current theories state that CA1, the main output stream of the hippocampus, would interplay inputs from EC and CA3 through network oscillations of different frequencies, namely high gamma (60-100 Hz; HG) and low gamma (30-50 Hz; LG), respectively, which tend to be nested in different phases of the theta cycle. In the present dissertation we use a freely available online dataset to make extensive computational analyses aimed at reproducing classical and recent results about the activity of place cells in the hippocampus of freely moving rats. In particular, we revisit the debate of whether phase precession is due to changes in firing frequency or space alone, and conclude that the phenomenon cannot be explained by either factor independently but by their joint influence. We also perform novel analyses investigating further characteristics of place cells in relation to network oscillations. We show that the strength of theta modulation of spikes only marginally affects the spatial information content of place cells, while the mean spiking theta phase has no influence on spatial information. Further analyses reveal that place cells are also modulated by theta when they fire outside the place field. Moreover, we find that the firing of place cells within the theta cycle is modulated by HG and LG amplitude in both CA1 and EC, matching cross-frequency coupling results found at the local field potential level. Additionally, the phase-amplitude coupling in CA1 associated with spikes inside the place field is characterized by amplitude modulation in the 40-80 Hz range. We conclude that place cell firing is embedded in large network states reflected in local field potential oscillations and suggest that their activity might be seen as a dynamic state rather than a fixed property of the cell.

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Cardiovascular diseases (CVDs) have reached an epidemic proportion in the US and worldwide with serious consequences in terms of human suffering and economic impact. More than one third of American adults are suffering from CVDs. The total direct and indirect costs of CVDs are more than $500 billion per year. Therefore, there is an urgent need to develop noninvasive diagnostics methods, to design minimally invasive assist devices, and to develop economical and easy-to-use monitoring systems for cardiovascular diseases. In order to achieve these goals, it is necessary to gain a better understanding of the subsystems that constitute the cardiovascular system. The aorta is one of these subsystems whose role in cardiovascular functioning has been underestimated. Traditionally, the aorta and its branches have been viewed as resistive conduits connected to an active pump (left ventricle of the heart). However, this perception fails to explain many observed physiological results. My goal in this thesis is to demonstrate the subtle but important role of the aorta as a system, with focus on the wave dynamics in the aorta.

The operation of a healthy heart is based on an optimized balance between its pumping characteristics and the hemodynamics of the aorta and vascular branches. The delicate balance between the aorta and heart can be impaired due to aging, smoking, or disease. The heart generates pulsatile flow that produces pressure and flow waves as it enters into the compliant aorta. These aortic waves propagate and reflect from reflection sites (bifurcations and tapering). They can act constructively and assist the blood circulation. However, they may act destructively, promoting diseases or initiating sudden cardiac death. These waves also carry information about the diseases of the heart, vascular disease, and coupling of heart and aorta. In order to elucidate the role of the aorta as a dynamic system, the interplay between the dominant wave dynamic parameters is investigated in this study. These parameters are heart rate, aortic compliance (wave speed), and locations of reflection sites. Both computational and experimental approaches have been used in this research. In some cases, the results are further explained using theoretical models.

The main findings of this study are as follows: (i) developing a physiologically realistic outflow boundary condition for blood flow modeling in a compliant vasculature; (ii) demonstrating that pulse pressure as a single index cannot predict the true level of pulsatile workload on the left ventricle; (iii) proving that there is an optimum heart rate in which the pulsatile workload of the heart is minimized and that the optimum heart rate shifts to a higher value as aortic rigidity increases; (iv) introducing a simple bio-inspired device for correction and optimization of aortic wave reflection that reduces the workload on the heart; (v) deriving a non-dimensional number that can predict the optimum wave dynamic state in a mammalian cardiovascular system; (vi) demonstrating that waves can create a pumping effect in the aorta; (vii) introducing a system parameter and a new medical index, Intrinsic Frequency, that can be used for noninvasive diagnosis of heart and vascular diseases; and (viii) proposing a new medical hypothesis for sudden cardiac death in young athletes.

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With the increase in load demand for various sectors, protection and safety of the network are key factors that have to be taken into consideration over the electric grid and distribution network. A phasor Measuring unit is an Intelligent electronics device that collects the data in the form of a real-time synchrophasor with a precise time tag using GPS (Global positioning system) and transfers the data to the grid command to monitor and assess the data. The measurements made by PMU have to be very precise to protect the relays and measuring equipment according to the IEEE 60255-118-1(2018). As a device PMU is very expensive to research and develop new functionalities there is a need to find an alternative to working with. Hence many open source virtual libraries are available to replicate the exact function of PMU in the virtual environment(Software) to continue the research on multiple objectives, providing the very least error results when verified. In this thesis, I executed performance and compliance verification of the virtual PMU which was developed using the I-DFT (Interpolated Discrete Fourier transforms) C-class algorithm in MATLAB. In this thesis, a test environment has been developed in MATLAB and tested the virtually developed PMU on both steady state and dynamic state for verifying the latest standard compliance(IEEE-60255-118-1).

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The simultaneous design of the steady-state and dynamic performance of a process has the ability to satisfy much more demanding dynamic performance criteria than the design of dynamics only by the connection of a control system. A method for designing process dynamics based on the use of a linearised systems' eigenvalues has been developed. The eigenvalues are associated with system states using the unit perturbation spectral resolution (UPSR), characterising the dynamics of each state. The design method uses a homotopy approach to determine a final design which satisfies both steady-state and dynamic performance criteria. A highly interacting single stage forced circulation evaporator system, including control loops, was designed by this method with the goal of reducing the time taken for the liquid composition to reach steady-state. Initially the system was successfully redesigned to speed up the eigenvalue associated with the liquid composition state, but this did not result in an improved startup performance. Further analysis showed that the integral action of the composition controller was the source of the limiting eigenvalue. Design changes made to speed up this eigenvalue did result in an improved startup performance. The proposed approach provides a structured way to address the design-control interface, giving significant insight into the dynamic behaviour of the system such that a systematic design or redesign of an existing system can be undertaken with confidence.

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This work deals with the numerical simulation of air stripping process for the pre-treatment of groundwater used in human consumption. The model established in steady state presents an exponential solution that is used, together with the Tau Method, to get a spectral approach of the solution of the system of partial differential equations associated to the model in transient state.

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Direct methanol fuel cell, DMFC, model, mass transport, Maxwell-Stefan, Flory-Huggins, crossover, polymer electrolyte membrane, Nafion

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Background: Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results: Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions: Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.

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A novel optimising controller is designed that leads a slow process from a sub-optimal operational condition to the steady-state optimum in a continuous way based on dynamic information. Using standard results from optimisation theory and discrete optimal control, the solution of a steady-state optimisation problem is achieved by solving a receding-horizon optimal control problem which uses derivative and state information from the plant via a shadow model and a state-space identifier. The paper analyzes the steady-state optimality of the procedure, develops algorithms with and without control rate constraints and applies the procedure to a high fidelity simulation study of a distillation column optimisation.

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Steady state and dynamic models have been developed and applied to the River Kennet system. Annual nitrogen exports from the land surface to the river have been estimated based on land use from the 1930s and the 1990s. Long term modelled trends indicate that there has been a large increase in nitrogen transport into the river system driven by increased fertiliser application associated with increased cereal production, increased population and increased livestock levels. The dynamic model INCA Integrated Nitrogen in Catchments. has been applied to simulate the day-to-day transport of N from the terrestrial ecosystem to the riverine environment. This process-based model generates spatial and temporal data and reproduces the observed instream concentrations. Applying the model to current land use and 1930s land use indicates that there has been a major shift in the short term dynamics since the 1930s, with increased river and groundwater concentrations caused by both non-point source pollution from agriculture and point source discharges. �