903 resultados para Anaerobic sequential batch reactor


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In this paper, the temperature of a pilot-scale batch reaction system is modeled towards the design of a controller based on the explicit model predictive control (EMPC) strategy -- Some mathematical models are developed from experimental data to describe the system behavior -- The simplest, yet reliable, model obtained is a (1,1,1)-order ARX polynomial model for which the mentioned EMPC controller has been designed -- The resultant controller has a reduced mathematical complexity and, according to the successful results obtained in simulations, will be used directly on the real control system in a next stage of the entire experimental framework

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The anaerobic process was efficient in organic matter removal. During the process, an interesting compound as quercetin was produced inside of reactor. Phylogenetic analysis showed the presence of phylotypes affiliated with gamma-Proteobacteria, Choroflexi, and Bacteroidetes. Archaea were represented by phylotypes belonging to the genus Methanosarcina and Methanosaeta.

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The design demands on water and sanitation engineers are rapidly changing. The global population is set to rise from 7 billion to 10 billion by 2083. Urbanisation in developing regions is increasing at such a rate that a predicted 56% of the global population will live in an urban setting by 2025. Compounding these problems, the global water and energy crises are impacting the Global North and South alike. High-rate anaerobic digestion offers a low-cost, low-energy treatment alternative to the energy intensive aerobic technologies used today. Widespread implementation however is hindered by the lack of capacity to engineer high-rate anaerobic digestion for the treatment of complex wastes such as sewage. This thesis utilises the Expanded Granular Sludge Bed bioreactor (EGSB) as a model system in which to study the ecology, physiology and performance of high-rate anaerobic digestion of complex wastes. The impacts of a range of engineered parameters including reactor geometry, wastewater type, operating temperature and organic loading rate are systematically investigated using lab-scale EGSB bioreactors. Next generation sequencing of 16S amplicons is utilised as a means of monitoring microbial ecology. Microbial community physiology is monitored by means of specific methanogenic activity testing and a range of physical and chemical methods are applied to assess reactor performance. Finally, the limit state approach is trialled as a method for testing the EGSB and is proposed as a standard method for biotechnology testing enabling improved process control at full-scale. The arising data is assessed both qualitatively and quantitatively. Lab-scale reactor design is demonstrated to significantly influence the spatial distribution of the underlying ecology and community physiology in lab-scale reactors, a vital finding for both researchers and full-scale plant operators responsible for monitoring EGSB reactors. Recurrent trends in the data indicate that hydrogenotrophic methanogenesis dominates in high-rate anaerobic digestion at both full- and lab-scale when subject to engineered or operational stresses including low-temperature and variable feeding regimes. This is of relevance for those seeking to define new directions in fundamental understanding of syntrophic and competitive relations in methanogenic communities and also to design engineers in determining operating parameters for full-scale digesters. The adoption of the limit state approach enabled identification of biological indicators providing early warning of failure under high-solids loading, a vital insight for those currently working empirically towards the development of new biotechnologies at lab-scale.

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Natural language processing has achieved great success in a wide range of ap- plications, producing both commercial language services and open-source language tools. However, most methods take a static or batch approach, assuming that the model has all information it needs and makes a one-time prediction. In this disser- tation, we study dynamic problems where the input comes in a sequence instead of all at once, and the output must be produced while the input is arriving. In these problems, predictions are often made based only on partial information. We see this dynamic setting in many real-time, interactive applications. These problems usually involve a trade-off between the amount of input received (cost) and the quality of the output prediction (accuracy). Therefore, the evaluation considers both objectives (e.g., plotting a Pareto curve). Our goal is to develop a formal understanding of sequential prediction and decision-making problems in natural language processing and to propose efficient solutions. Toward this end, we present meta-algorithms that take an existent batch model and produce a dynamic model to handle sequential inputs and outputs. Webuild our framework upon theories of Markov Decision Process (MDP), which allows learning to trade off competing objectives in a principled way. The main machine learning techniques we use are from imitation learning and reinforcement learning, and we advance current techniques to tackle problems arising in our settings. We evaluate our algorithm on a variety of applications, including dependency parsing, machine translation, and question answering. We show that our approach achieves a better cost-accuracy trade-off than the batch approach and heuristic-based decision- making approaches. We first propose a general framework for cost-sensitive prediction, where dif- ferent parts of the input come at different costs. We formulate a decision-making process that selects pieces of the input sequentially, and the selection is adaptive to each instance. Our approach is evaluated on both standard classification tasks and a structured prediction task (dependency parsing). We show that it achieves similar prediction quality to methods that use all input, while inducing a much smaller cost. Next, we extend the framework to problems where the input is revealed incremen- tally in a fixed order. We study two applications: simultaneous machine translation and quiz bowl (incremental text classification). We discuss challenges in this set- ting and show that adding domain knowledge eases the decision-making problem. A central theme throughout the chapters is an MDP formulation of a challenging problem with sequential input/output and trade-off decisions, accompanied by a learning algorithm that solves the MDP.

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The increasing attention to environmental issues of recent times encourages us to find new methods for the production of energy from renewable sources, and to improve existing ones, increasing their energy yield. Most of the waste and agricultural residues, with a high content of lignin and non-hydrolysable polymers, cannot be effectively transformed into biofuels with existing technology. The purpose of the study was to develop a new thermochemical/ biological process (named Py-AD) for the valorization of scarcely biodegradable substances. A complete continuous prototype was design built and run for 1 year. This consists into a slow pyrolysis system coupled with two sequential digesters and showed to produce a clean pyrobiogas (a biogas with significant amount of C2-C3 hydrocarbons and residual CO/H2), biochar and bio-oil. Py-AD yielded 31.7% w/w biochar 32.5% w/w oil and 24.8% w/w pyrobiogas. The oil condensate obtained was fractionated in its aqueous and organic fraction (87% and 13% respectively). Subsequently, the anaerobic digestion of aqueous fraction was tested in a UASB reactor, for 180 days, in increasing organic loading rate (OLR). The maximum convertible concentration without undergoing instability phenomena and with complete degradation of pyrogenic chemicals was 1.25 gCOD L digester-1 d-1. The final yield of biomethane was equal to 40% of the theoretical yield and with a noticeable additional production equal to 20% of volatile fatty acids. The final results confirm that anaerobic digestion can be used as a useful tool for cleaning of slow pyrolysis products (both gas and condensable fraction) and the obtaining of relatively clean pyrobiogas that could be directly used in internal combustion engine.

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THE PURPOSE OF THIS STUDY WAS TO PROPOSE A SPECIFIC LACTATE MINIMUM TEST FOR ELITE BASKETBALL PLAYERS CONSIDERING THE: Running Anaerobic Sprint Test (RAST) as a hyperlactatemia inductor, short distances (specific distance, 20 m) during progressive intensity and mathematical analysis to interpret aerobic and anaerobic variables. The basketball players were assigned to four groups: All positions (n=26), Guard (n= 7), Forward (n=11) and Center (n=8). The hyperlactatemia elevation (RAST) method consisted of 6 maximum sprints over 35 m separated by 10 s of recovery. The progressive phase of the lactate minimum test consisted of 5 stages controlled by an electronic metronome (8.0, 9.0, 10.0, 11.0 and 12.0 km/h) over a 20 m distance. The RAST variables and the lactate values were analyzed using visual and mathematical models. The intensity of the lactate minimum test, determined by a visual method, reduced in relation to polynomial fits (2nd degree) for the Small Forward positions and General groups. The Power and Fatigue Index values, determined by both methods, visual and 3rd degree polynomial, were not significantly different between the groups. In conclusion, the RAST is an excellent hyperlactatemia inductor and the progressive intensity of lactate minimum test using short distances (20 m) can be specifically used to evaluate the aerobic capacity of basketball players. In addition, no differences were observed between the visual and polynomial methods for RAST variables, but lactate minimum intensity was influenced by the method of analysis.

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The main aim of this investigation was to verify the relationship of the variables measured during a 3-minute all-out test with aerobic (i.e., peak oxygen uptake [(Equation is included in full-text article.)] and intensity corresponding to the lactate minimum [LMI]) and anaerobic parameters (i.e., anaerobic work) measured during a 400-m maximal performance. To measure force continually and to avoid the possible influences caused by turns, the 3-minute all-out effort was performed in tethered swimming. Thirty swimmers performed the following tests: (a) a 3-minute all-out tethered swimming test to determine the final force (equivalent to critical force: CF3-MIN) and the work performed above CF3-MIN (W'3-MIN), (b) a LMI protocol to determine the LMI during front crawl swimming, and (c) a 400-m maximal test to determine the (Equation is included in full-text article.)and total anaerobic contribution (WANA). Correlations between the variables were tested using the Pearson's correlation test (p ≤ 0.05). CF3-MIN (73.9 ± 13.2 N) presented a high correlation with the LMI (1.33 ± 0.08 m·s; p = 0.01) and (Equation is included in full-text article.)(4.5 ± 1.2 L·min; p = 0.01). However, the W'3-MIN (1,943.2 ± 719.2 N·s) was only moderately correlated with LMI (p = 0.02) and (Equation is included in full-text article.)(p = 0.01). In summary, CF3-MIN determined during the 3-minute all-out effort is associated with oxidative metabolism and can be used to estimate the aerobic capacity of swimmers. In contrast, the anaerobic component of this model (W'3-MIN) is not correlated with WANA.

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The biodegradability of animal wastes production was evaluated through a simplified methodology that allowed the verification of the applicability of anaerobic processes. The experiments were performed in bath reactors, with granular sludge of three origins: UASB reactor treating dairy effluent, UASB reactor treating swine effluent and UASB reactor treating effluent of slaughterhouse of poultry. The experiments (1) - dairy effluent and poultry slaughterhouse non-adapted sludge; (2) -swine effluent and poultry slaughterhouse non-adapted sludge; (3) - dairy effluent and poultry slaughterhouse adapted sludge; (4) - swine effluent and poultry slaughterhouse adapted sludge; (5) - dairy effluent and dairy sludge, and (6) - swine effluent and swine sludge were performed in Incubator Shaker, at a temperature of 35 °C, under agitation at a 150 rpm, for 5 minutes, every 1 hour. A substrat:biomass relationship of 0.5 was used. Kinetic models of Monod, Zero Order, First and Second Order were tested and it was verified that the First Order model provided the best adjustment. The apparent First Order kinetic parameter (k1) was estimated for the experiments 1; 2; 3; 4; 5, and 6, as 2.51 x 10-2; 2.49 x 10-2; 1.90 x 10-2; 3.09 x 10-2; 2.54 x 10-2; 4.09 x 10-2 h-1, respectively.

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Universidade Estadual de Campinas . Faculdade de Educação Física

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Physiological and biochemical aspects of assai palm during seed germination and early seedling growth were investigated. Seeds collected from plants growing in flooded and upland forests were used to determine the influence of normoxic (aerobic) and anoxic (anaerobic) conditions in germination and the initial and average time of development in the roots and shoots. After 75 days, seedlings germinated under normoxia were transferred to trays and submitted to flooding. Seed reserves (lipids, proteins, soluble sugars and starch) were monitored for quiescent and germinated seeds maintained under normoxic and anoxic conditions, as well as after 5, 10 and 20 days of seedling growth. Alcohol dehydrogenase (ADH) activity was quantified in roots and leaves of seedlings without or with flooding (partial and total). Seeds were not able to germinate under anoxia. Different strategies of storage mobilization of lipids, proteins, soluble sugars and starch were observed in seeds of each environment. ADH activity was induced by anoxia, with the highest level observed in the leaves. This study showed that, under normoxic conditions, the best developmental performance of assai palm seeds, from flooded or upland forest areas, during germination was associated with primary metabolites mobilization and seedling flooding tolerance with increased ADH activity. We conclude that the assai palm is well adapted to the anoxic conditions provoked by flooding.

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In order to verify the influence of chronic and acute ambient oxygen levels from egg to adult stage of the zebrafish, in vivo oxygen consumption (MO2), critical tensions of oxygen (Pcrit), heart rate (fH) and total body lactate concentration (Lc) were determined for Danio rerio (Hamilton, 1822) raised at 28 °C under normoxic (7.5 mgO2.L-1 or 80 mm.Hg-1) and hypoxic conditions (4.3 mgO2.L-1) and exposed to acute hypoxia during different developmental stages. Our findings confirmed that very early stages do not respond effectively to ambient acute hypoxia. However, after the stage corresponding to the age of 30 days, D. rerio was able to respond to acute hypoxia through effective physiological mechanisms involving aerobic and anaerobic metabolism. Such responses were more efficient for the fishes reared under hypoxia which showed that D. rerio survival capability increased during acclimation to mild hypoxia. Measurements of body mass and length showed that moderate hypoxia did not affect growth significantly until the fish reached the stage of 60 days. Moreover, a growth delay was verified for the hypoxic-reared animals. Also, the D. rerio eggs-to-larvae survival varied from 87.7 to 62.4% in animals reared under normoxia and mild hypoxia, respectively. However, the surviving animals raised under moderated hypoxia showed a better aptitude to regulate aerobic and anaerobic capacities when exposed to acute hypoxia.

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The n→π* absorption transition of formaldehyde in water is analyzed using combined and sequential classical Monte Carlo (MC) simulations and quantum mechanics (QM) calculations. MC simulations generate the liquid solute-solvent structures for subsequent QM calculations. Using time-dependent density functional theory in a localized set of gaussian basis functions (TD-DFT/6-311++G(d,p)) calculations are made on statistically relevant configurations to obtain the average solvatochromic shift. All results presented here use the electrostatic embedding of the solvent. The statistically converged average result obtained of 2300 cm-1 is compared to previous theoretical results available. Analysis is made of the effective dipole moment of the hydrogen-bonded shell and how it could be held responsible for the polarization of the solvent molecules in the outer solvation shells.

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The photocatalytic degradation of phenol in aqueous suspensions of TiO2 under different salt concentrations in an annular reactor has been investigated. In all cases, complete removal of phenol and mineralization degrees above 90% were achieved. The reactor operational parameters were optimized and its hydrodynamics characterized in order to couple mass balance equations with kinetic ones. The photodegradation of the organics followed a Langmuir-Hinshelwood-Hougen-Watson lumped kinetics. From GC/MS analyses, several intermediates formed during oxidation have been identified. The main ones were catechol, hydroquinone, and 3-phenyl-2-propenal, in this order. The formation of negligible concentrations of 4-chlorophenol was observed only in high salinity medium. Acute toxicity was determined by using Artemia sp. as the test organism, which indicated that intermediate products were all less toxic than phenol and a significant abatement of the overall toxicity was accomplished, regardless of the salt concentration.

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This paper describes a sequential injection chromatography procedure for determination of picloram in waters exploring the low backpressure of a 2.5 cm long monolithic C18 column. Separation of the analyte from the matrix was achieved in less than 60 s using a mobile phase composed by 20:80 (v v-1) acetonitrile:5.0 mmol L-1 H3PO4 and flow rate of 30 μL s-1. Detection was made at 223 nm with a 40 mm optical path length cell. The limits of detection and quantification were 33 and 137 μg L-1, respectively. The proposed method is sensitive enough to monitor the maximum concentration level for picloram in drinking water (500 μg L-1). The sampling frequency is 60 analyses per hour, consuming only 300 μL of acetonitrile per analysis. The proposed methodology was applied to spiked river water samples and no statistically significant differences were observed in comparison to a conventional HPLC-UV method.

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Biomass Refinery is a sequential of eleven thermochemical processes and one biological process with two initial basic treatments: prehydrolysis for lignocellulosics and low temperature conversion for biomass with medium-to-high content of lipids and proteins. The other ten processes are: effluent treatment plant, furfural plant, biodiesel plant, cellulignin dryer, calcination, fluidized bed boiler, authotermal reforming of cellulignin for syngas production, combined cycle of two-stroke low-speed engine or syngas turbine with fluidized bed boiler heat recovery, GTL technologies and ethanol from cellulose, prehydrolysate and syngas. Any kind of biomass such as wood, agricultural residues, municipal solid waste, seeds, cakes, sludges, excrements and used tires can be processed at the Biomass Refinery. Twelve basic products are generated such as cellulignin, animal feed, electric energy, fuels (ethanol, crude oil, biodiesel, char), petrochemical substitutes, some materials (ash, gypsum, fertilizers, silica, carbon black) and hydrogen. The technology is clean with recovery of energy and reuse of water, acid and effluents. Based on a holistic integration of various disciplines Biomass Refinery maximizes the simultaneous production of food, electric energy, liquid fuels and chemical products and some materials, achieving a competitive position with conventional and fossil fuel technologies, as well as payment capacity for biomass production. Biomass Refinery has a technical economical capability to complement the depletion of the conventional petroleum sources and to capture its GHGs resulting a biomass + petroleum ""green"" combination.