931 resultados para sequential batch


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A mathematical model that describes the operation of a sequential leach bed process for anaerobic digestion of organic fraction of municipal solid waste (MSW) is developed and validated. This model assumes that ultimate mineralisation of the organic component of the waste occurs in three steps, namely solubilisation of particulate matter, fermentation to volatile organic acids (modelled as acetic acid) along with liberation of carbon dioxide and hydrogen, and methanogenesis from acetate and hydrogen. The model incorporates the ionic equilibrium equations arising due to dissolution of carbon dioxide, generation of alkalinity from breakdown of solids and dissociation of acetic acid. Rather than a charge balance, a mass balance on the hydronium and hydroxide ions is used to calculate pH. The flow of liquid through the bed is modelled as occurring through two zones-a permeable zone with high flushing rates and the other more stagnant. Some of the kinetic parameters for the biological processes were obtained from batch MSW digestion experiments. The parameters for flow model were obtained from residence time distribution studies conducted using tritium as a tracer. The model was validated using data from leach bed digestion experiments in which a leachate volume equal to 10% of the fresh waste bed volume was sequenced. The model was then tested, without altering any kinetic or flow parameters, by varying volume of leachate that is sequenced between the beds. Simulations for sequencing/recirculating 5 and 30% of the bed volume are presented and compared with experimental results. (C) 2002 Elsevier Science B.V. All rights reserved.

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The main aim of the work is to investigate sequential pyrolysis of willow SRC using two different heating rates (25 and 1500 °C/min) between 320 and 520 °C. Thermogravimetric analysis (TGA) and pyrolysis - gas chromatography - mass spectroscopy (Py-GC-MS) have been used for this analysis. In addition, laboratory scale processing has been undertaken to compare product distribution from fast and slow pyrolysis at 500 °C. Fast pyrolysis was carried out using a 1 kg/h continuous bubbling fluidized bed reactor, and slow pyrolysis using a 100 g batch reactor. Findings from this study show that heating rate and pyrolysis temperatures have a significant influence on the chemical content of decomposition products. From the analytical sequential pyrolysis, an inverse relationship was seen between the total yield of furfural (at high heating rates) and 2-furanmethanol (at low heating rates). The total yield of 1,2-dihydroxybenzene (catechol) was found to be significant higher at low heating rates. The intermediates of catechol, 2-methoxy-4-(2-propenyl)phenol (eugenol); 2-methoxyphenol (guaiacol); 4-Hydroxy-3,5-dimethoxybenzaldehyde (syringaldehyde) and 4-hydroxy-3-methoxybenzaldehyde (vanillin), were found to be highest at high heating rates. It was also found that laboratory scale processing alters the pyrolysis bio-oil chemical composition, and the proportions of pyrolysis product yields. The GC-MS/FID analysis of fast and slow pyrolysis bio-oils reveals significant differences. © 2011 Elsevier Ltd. All rights reserved.

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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 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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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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This work describes a photo-reactor to perform in line degradation of organic compounds by photo-Fenton reaction using Sequential Injection Analysis (SIA) system. A copper phthalocyanine-3,4',4²,4²¢-tetrasulfonic acid tetrasodium salt dye solution was used as a model compound for the phthalocyanine family, whose pigments have a large use in automotive coatings industry. Based on preliminary tests, 97% of color removal was obtained from a solution containing 20 µmol L-1 of this dye.

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We examined the sequence, order or steps of hygienic behavior (HB) from pin-killed pupae until the removal of them by the bees. We conducted our study with four colonies of Apis mellifera carnica in Germany and made four repetitions. The pin-killing method was used for evaluation of the HB of bees. The data were collected every 2 h after perforation, totaling 13 observations. Additionally, for one hygienic colony and another non-hygienic colony, individual analyses of each dead pupa were made at every observation, including all details, steps or sequences of HB. The bees recognize the cells containing dead pupae within 2 h after perforation, initially making a hole in the capping, which is the beginning of HB. Uncapping of the dead brood cell reached maximum values from 4 to 6 h after perforation; after 24 h, practically all cells were already uncapped. Another variable, called brood partially removed, was analyzed 4 h after perforation, after the cells had been perforated, which involved uncapping, followed by partial or total removal of the brood. Maximum values of brood partially removed were found 10 h after perforation, though such cells could be found up to 48 h after perforation. The most frequent sequence of events in both colonies was: capped cell -> punctured cell. brood partially removed -> empty cell. A new model of three pairs of recessive genes (uncapping u1, u2 and remover r) was proposed in order to explain the genetic control of the HB in Apis mellifera. We recommend evaluating HB 24 h after perforation and using a correction factor to compensate for control removal levels. We found a series of details of HB, which allow a study of how various factors may affect the sequence of the activities involved in HB and investigation of the genetics that controls this process.

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Background: Without intensive selection, the majority of bovine oocytes submitted to in vitro embryo production (IVP) fail to develop to the blastocyst stage. This is attributed partly to their maturation status and competences. Using the Affymetrix GeneChip Bovine Genome Array, global mRNA expression analysis of immature (GV) and in vitro matured (IVM) bovine oocytes was carried out to characterize the transcriptome of bovine oocytes and then use a variety of approaches to determine whether the observed transcriptional changes during IVM was real or an artifact of the techniques used during analysis. Results: 8489 transcripts were detected across the two oocyte groups, of which similar to 25.0% (2117 transcripts) were differentially expressed (p < 0.001); corresponding to 589 over-expressed and 1528 under-expressed transcripts in the IVM oocytes compared to their immature counterparts. Over expression of transcripts by IVM oocytes is particularly interesting, therefore, a variety of approaches were employed to determine whether the observed transcriptional changes during IVM were real or an artifact of the techniques used during analysis, including the analysis of transcript abundance in oocytes in vitro matured in the presence of a-amanitin. Subsets of the differentially expressed genes were also validated by quantitative real-time PCR (qPCR) and the gene expression data was classified according to gene ontology and pathway enrichment. Numerous cell cycle linked (CDC2, CDK5, CDK8, HSPA2, MAPK14, TXNL4B), molecular transport (STX5, STX17, SEC22A, SEC22B), and differentiation (NACA) related genes were found to be among the several over-expressed transcripts in GV oocytes compared to the matured counterparts, while ANXA1, PLAU, STC1and LUM were among the over-expressed genes after oocyte maturation. Conclusion: Using sequential experiments, we have shown and confirmed transcriptional changes during oocyte maturation. This dataset provides a unique reference resource for studies concerned with the molecular mechanisms controlling oocyte meiotic maturation in cattle, addresses the existing conflicting issue of transcription during meiotic maturation and contributes to the global goal of improving assisted reproductive technology.

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This study proposes a simplified mathematical model to describe the processes occurring in an anaerobic sequencing batch biofilm reactor (ASBBR) treating lipid-rich wastewater. The reactor, subjected to rising organic loading rates, contained biomass immobilized cubic polyurethane foam matrices, and was operated at 32 degrees C +/- 2 degrees C, using 24-h batch cycles. In the adaptation period, the reactor was fed with synthetic substrate for 46 days and was operated without agitation. Whereas agitation was raised to 500 rpm, the organic loading rate (OLR) rose from 0.3 g chemical oxygen demand (COD) . L(-1) . day(-1) to 1.2 g COD . L(-1) . day(-1). The ASBBR was fed fat-rich wastewater (dairy wastewater), in an operation period lasting for 116 days, during which four operational conditions (OCs) were tested: 1.1 +/- 0.2 g COD . L(-1) . day(-1) (OC1), 4.5 +/- 0.4 g COD . L(-1) . day(-1) (OC2), 8.0 +/- 0.8 g COD . L(-1) . day(-1) (OC3), and 12.1 +/- 2.4 g COD . L(-1) . day(-1) (OC4). The bicarbonate alkalinity (BA)/COD supplementation ratio was 1:1 at OC1, 1:2 at OC2, and 1:3 at OC3 and OC4. Total COD removal efficiencies were higher than 90%, with a constant production of bicarbonate alkalinity, in all OCs tested. After the process reached stability, temporal profiles of substrate consumption were obtained. Based on these experimental data a simplified first-order model was fit, making possible the inference of kinetic parameters. A simplified mathematical model correlating soluble COD with volatile fatty acids (VFA) was also proposed, and through it the consumption rates of intermediate products as propionic and acetic acid were inferred. Results showed that the microbial consortium worked properly and high efficiencies were obtained, even with high initial substrate concentrations, which led to the accumulation of intermediate metabolites and caused low specific consumption rates.

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The dynamic polarizability and optical absorption spectrum of liquid water in the 6-15 eV energy range are investigated by a sequential molecular dynamics (MD)/quantum mechanical approach. The MD simulations are based on a polarizable model for liquid water. Calculation of electronic properties relies on time-dependent density functional and equation-of-motion coupled-cluster theories. Results for the dynamic polarizability, Cauchy moments, S(-2), S(-4), S(-6), and dielectric properties of liquid water are reported. The theoretical predictions for the optical absorption spectrum of liquid water are in good agreement with experimental information.

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The nuclear isotropic shielding constants sigma((17)O) and sigma((13)C) of the carbonyl bond of acetone in water at supercritical (P=340.2 atm and T=673 K) and normal water conditions have been studied theoretically using Monte Carlo simulation and quantum mechanics calculations based on the B3LYP/6-311++G(2d,2p) method. Statistically uncorrelated configurations have been obtained from Monte Carlo simulations with unpolarized and in-solution polarized solute. The results show that solvent effects on the shielding constants have a significant contribution of the electrostatic interactions and that quantitative estimates for solvent shifts of shielding constants can be obtained modeling the water molecules by point charges (electrostatic embedding). In supercritical water, there is a decrease in the magnitude of sigma((13)C) but a sizable increase in the magnitude of sigma((17)O) when compared with the results obtained in normal water. It is found that the influence of the solute polarization is mild in the supercritical regime but it is particularly important for sigma((17)O) in normal water and its shielding effect reflects the increase in the average number of hydrogen bonds between acetone and water. Changing the solvent environment from normal to supercritical water condition, the B3LYP/6-311++G(2d,2p) calculations on the statistically uncorrelated configurations sampled from the Monte Carlo simulation give a (13)C chemical shift of 11.7 +/- 0.6 ppm for polarized acetone in good agreement with the experimentally inferred result of 9-11 ppm. (C) 2008 American Institute of Physics.

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The electronic properties of liquid ammonia are investigated by a sequential molecular dynamics/quantum mechanics approach. Quantum mechanics calculations for the liquid phase are based on a reparametrized hybrid exchange-correlation functional that reproduces the electronic properties of ammonia clusters [(NH(3))(n); n=1-5]. For these small clusters, electron binding energies based on Green's function or electron propagator theory, coupled cluster with single, double, and perturbative triple excitations, and density functional theory (DFT) are compared. Reparametrized DFT results for the dipole moment, electron binding energies, and electronic density of states of liquid ammonia are reported. The calculated average dipole moment of liquid ammonia (2.05 +/- 0.09 D) corresponds to an increase of 27% compared to the gas phase value and it is 0.23 D above a prediction based on a polarizable model of liquid ammonia [Deng , J. Chem. Phys. 100, 7590 (1994)]. Our estimate for the ionization potential of liquid ammonia is 9.74 +/- 0.73 eV, which is approximately 1.0 eV below the gas phase value for the isolated molecule. The theoretical vertical electron affinity of liquid ammonia is predicted as 0.16 +/- 0.22 eV, in good agreement with the experimental result for the location of the bottom of the conduction band (-V(0)=0.2 eV). Vertical ionization potentials and electron affinities correlate with the total dipole moment of ammonia aggregates. (c) 2008 American Institute of Physics.

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An analytical procedure for multiple standard additions of arsenic species using sequential injection analysis (SIA) is proposed for their quantification in seafood extracts. SIA presented flexibility for generating multiple specie standards at the ng mL(-1) concentration level by adding different volumes of As(III), As(V), monomethylarsonic (MMA) and dimethylarsinic (DMA) to the sample. The mixed sample plus standard solutions were delivered from SIA to fill the HPLC injection loop. Subsequently, As species were separated by HPLC and analyzed by atomic fluorescence spectrometry (AFS). The proposed system comprised two independently controlled modules, with the HPLC loop acting as the intermediary device. The analytical frequency was enhanced by combining the actions of both modules. While the added sample was flowing through the chromatographic column towards the detection system, the SIA program started performing the standard additions to another sample. The proposed method was applied to spoiled seafood extracts. Detection limits based on 3 sigma for As(III), As(V), MMA and DMA were 0.023, 0.39, 0.45 and 1.0 ng mL(-1), respectively. (C) 2011 Elsevier B.V. All rights reserved.

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A new procedure for spectrofluorimetric determination of free and total glycerol in biodiesel samples is presented. It is based on the oxidation of glycerol by periodate, forming formaldehyde, which reacts with acetylacetone, producing the luminescent 3,5-diacetyl-1,4-dihydrolutidine. A flow system with solenoid micro-pumps is proposed for solution handling. Free glycerol was extracted off-line from biodiesel samples with water, and total glycerol was converted to free glycerol by saponification with sodium ethylate under sonication. For free glycerol, a linear response was observed from 5 to 70 mg L(-1) with a detection limit of 0.5 mg L(-1), which corresponds to 2 mg kg(-1) in biodiesel. The coefficient of variation was 0.9% (20 mg L(-1), n = 10). For total glycerol, samples were diluted on-line, and the linear response range was 25 to 300 mg L(-1). The detection limit was 1.4 mg L(-1) (2.8 mg kg(-1) in biodiesel) with a coefficient of variation of 1.4% (200 mg L(-1), n = 10). The sampling rate was ca. 35 samples h(-1) and the procedure was applied to determination of free and total glycerol in biodiesel samples from soybean, cottonseed, and castor beans.

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An improved flow-based procedure is proposed for turbidimetric sulphate determination in waters. The flow system was designed with solenoid micro-pumps in order to improve mixing conditions and minimize reagent consumption as well as waste generation. Stable baselines were observed in view of the pulsed flow characteristic of the systems designed with solenoid micro-pumps, thus making the use of washing solutions unnecessary. The nucleation process was improved by stopping the flow prior to the measurement, thus avoiding the need of sulphate addition. When a 1-cm optical path flow cell was employed, linear response was achieved within 20-200 mg L(-1), described by the equation S = -0.0767 + 0.00438C (mg L(-1)), r = 0.999. The detection limit was estimated as 3 mg L(-1) at the 99.7% confidence level and the coefficient of variation was 2.4% (n = 20). The sampling rate was estimated as 33 determinations per hour. A long pathlength (100-cm) flow cell based on a liquid core waveguide was exploited to increase sensitivity in turbidimetry. Baseline drifts were avoided by a periodical washing step with EDTA in alkaline medium. Linear response was observed within 7-16 mg L(-1), described by the equation S = -0.865 + 0.132C (mg L(-1)), r = 0.999. The detection limit was estimated as 150 mu g L(-1) at the 99.7% confidence level and the coefficient of variation was 3.0% (n = 20). The sampling rate was estimated as 25 determinations per hour. The results obtained for freshwater and rain water samples were in agreement with those achieved by batch turbidimetry at the 95% confidence level. (C) 2008 Elsevier B.V All rights reserved.