Liquid transportation and distribution during (re)wetting : impact on coated papers in printing

In many industrial applications, such as the printing and coatings industry, wetting of porous materials by liquids includes not only imbibition and permeation into the bulk but also surface spreading and evaporation. By understanding these phenomena, valuable information can be obtained for improved process control, runnability and printability, in which liquid penetration and subsequent drying play important quality and economic roles. Knowledge of the position of the wetting front and the distribution/degree of pore filling within the structure is crucial in describing the transport phenomena involved. Although exemplifying paper as a porous medium in this work, the generalisation to dynamic liquid transfer onto a surface, including permeation and imbibition into porous media, is of importance to many industrial and naturally occurring environmental processes. This thesis explains the phenomena in the field of heatset web offset printing but the content and the analyses are applicable in many other printing methods and also other technologies where water/moisture monitoring is crucial in order to have a stable process and achieve high quality end products. The use of near-infrared technology to study the water and moisture response of porous pigmented structures is presented. The use of sensitive surface chemical and structural analysis, as well as the internal structure investigation of a porous structure, to inspect liquid wetting and distribution, complements the information obtained by spectroscopic techniques. Strong emphasis has been put on the scale of measurement, to filter irrelevant information and to understand the relationship between interactions involved. The near-infrared spectroscopic technique, presented here, samples directly the changes in signal absorbance and its variation in the process at multiple locations in a print production line. The in-line non-contact measurements are facilitated by using several diffuse reflectance probes, giving the absolute water/moisture content from a defined position in the dynamic process in real-time. The nearinfrared measurement data illustrate the changes in moisture content as the paper is passing through the printing nips and dryer, respectively, and the analysis of the mechanisms involved highlight the roles of the contacting surfaces and the relative liquid carrier properties of both non-image and printed image areas. The thesis includes laboratory studies on wetting of porous media in the form of coated paper and compressed pigment tablets by mono-, dual-, and multi-component liquids, and paper water/moisture content analysis in both offline and online conditions, thus also enabling direct sampling of temporal water/moisture profiles from multiple locations. One main focus in this thesis was to establish a measurement system which is able to monitor rapid changes in moisture content of paper. The study suggests that near-infrared diffuse reflectance spectroscopy can be used as a moisture sensitive system and to provide accurate online qualitative indicators, but, also, when accurately calibrated, can provide quantification of water/moisture levels, its distribution and dynamic liquid transfer. Due to the high sensitivity, samples can be measured with excellent reproducibility and good signal to noise ratio. Another focus of this thesis was on the evolution of the moisture content, i.e. changes in moisture content referred to (re)wetting, and liquid distribution during printing of coated paper. The study confirmed different wetting phases together with the factors affecting each phase both for a single droplet and a liquid film applied on a porous substrate. For a single droplet, initial capillary driven imbibition is followed by equilibrium pore filling and liquid retreat by evaporation. In the case of a liquid film applied on paper, the controlling factors defining the transportation were concluded to be the applied liquid volume in relation to surface roughness, capillarity and permeability of the coating giving the liquid uptake capacity. The printing trials confirmed moisture gradients in the printed sheet depending on process parameters such as speed, fountain solution dosage and drying conditions as well as the printed layout itself. Uneven moisture distribution in the printed sheet was identified to be one of the sources for waving appearance and the magnitude of waving was influenced by the drying conditions.

Calibration uncertainty estimation for internal aerodynamic balance

Aerodynamic balances are employed in wind tunnels to estimate the forces and moments acting on the model under test. This paper proposes a methodology for the assessment of uncertainty in the calibration of an internal multi-component aerodynamic balance. In order to obtain a suitable model to provide aerodynamic loads from the balance sensor responses, a calibration is performed prior to the tests by applying known weights to the balance. A multivariate polynomial fitting by the least squares method is used to interpolate the calibration data points. The uncertainties of both the applied loads and the readings of the sensors are considered in the regression. The data reduction includes the estimation of the calibration coefficients, the predicted values of the load components and their corresponding uncertainties, as well as the goodness of fit.

Patterns of painting in satin bowerbirds Ptilonorhynchus violaceus and males' responses to changes in their paint

Satin bowerbirds Ptilonorhynchus violaceus have an elaborate multi-component sexual display, some components of which have been extensively studied. We describe a relatively unstudied component of this display, bower painting, and birds' responses to manipulations of their paint. Males of this species focus their display around a stick bower constructed on the forest floor which they decorate with a variety of objects and paint. Painting involves a male masticating plant material and wiping the plant-saliva mixture onto the inside walls of the bower; during courtship visits to bowers, females nibble at this paint. We found that 93% of 53 males painted their bowers at our study site and the time males spent painting their bowers accounted for 24% of their time at the bower. We experimentally removed and added paint to bowers to test whether males respond to these changes in their paint. Males gave more advertisement calls and spent less time manipulating sticks at the bower when we added fresh wet paint to their bowers compared to older dried paint or a control treatment. They did not respond to the removal of paint from their bowers, perhaps because it was primarily older dried paint that was removed. We also found that males painted more frequently when there was measurable wind in their bowers, which could have degraded the quality of the signal. Our findings indicate that fresh wet paint is more important to males than older dried paint and, together with previous work at this site, suggest that paint may act as a signal to females. Given that females nibble bower sticks during courtship, we suggest that bower paint may function as a chemical sexual signal rather than a visual signal.

Evaluation of uv spectrophotometry for estimation of nitrite and nitrate in nitrified urine

Water is a limited resource for which demand is growing. Contaminated water from inadequate wastewater treatment provides one of the greatest health challenges as it restricts development and increases poverty in emerging and developing countries. Therefore, the connection between wastewater and human health is linked to access to sanitation and to human waste disposal. Adequate sanitation is expected to create a barrier between disposed human excreta and sources of drinking water. Different approaches to wastewater management are required for different geographical regions and different stages of economic governance depending on the capacity to manage wastewater. Effective wastewater management can contribute to overcome the challenges of water scarcity. Separate collection of human urine at its source is one promising approach that strongly reduces the economic and load demands on wastewater treatment plants (WWTP). Treatment of source-separated urine appears as a sanitation system that is affordable, produces a valuable fertiliser, reduces pollution of water resources and promotes health. However, the technical realisation of urine separation still faces challenges. Biological hydrolysis of urea causes a strong increase of ammonia and pH. Under these conditions ammonia volatilises which can cause odour problems and significant nitrogen losses. The above problems can be avoided by urine stabilisation. Biological nitrification is a suitable process for stabilisation of urine. Urine is a highly concentrated nutrient solution which can lead to strong inhibition effects during bacterial nitrification. This can further lead to process instabilities. The major cause of instability is accumulation of the inhibitory intermediate compound nitrite, which could lead to process breakdown. Enhanced on-line nitrite monitoring can be applied in biological source-separated urine nitrification reactors as a sustainable and efficient way to improve the reactor performance, avoiding reactor failures and eventual loss of biological activity. Spectrophotometry appears as a promising candidate for the development and application of on-line nitrite monitoring. Spectroscopic methods together with chemometrics are presented in this work as a powerful tool for estimation of nitrite concentrations. Principal component regression (PCR) is applied for the estimation of nitrite concentrations using an immersible UV sensor and off-line spectra acquisition. The effect of particles and the effect of saturation, respectively, on the UV absorbance spectra are investigated. The analysis allows to conclude that (i) saturation has a substantial effect on nitrite estimation; (ii) particles appear to have less impact on nitrite estimation. In addition, improper mixing together with instabilities in the urine nitrification process appears to significantly reduce the performance of the estimation model.

A finite-population revenue management model and a risk-ratio procedure for the joint estimation of population size and parameters

Many dynamic revenue management models divide the sale period into a finite number of periods T and assume, invoking a fine-enough grid of time, that each period sees at most one booking request. These Poisson-type assumptions restrict the variability of the demand in the model, but researchers and practitioners were willing to overlook this for the benefit of tractability of the models. In this paper, we criticize this model from another angle. Estimating the discrete finite-period model poses problems of indeterminacy and non-robustness: Arbitrarily fixing T leads to arbitrary control values and on the other hand estimating T from data adds an additional layer of indeterminacy. To counter this, we first propose an alternate finite-population model that avoids this problem of fixing T and allows a wider range of demand distributions, while retaining the useful marginal-value properties of the finite-period model. The finite-population model still requires jointly estimating market size and the parameters of the customer purchase model without observing no-purchases. Estimation of market-size when no-purchases are unobservable has rarely been attempted in the marketing or revenue management literature. Indeed, we point out that it is akin to the classical statistical problem of estimating the parameters of a binomial distribution with unknown population size and success probability, and hence likely to be challenging. However, when the purchase probabilities are given by a functional form such as a multinomial-logit model, we propose an estimation heuristic that exploits the specification of the functional form, the variety of the offer sets in a typical RM setting, and qualitative knowledge of arrival rates. Finally we perform simulations to show that the estimator is very promising in obtaining unbiased estimates of population size and the model parameters.

Source separation techniques applied to linear prediction

The prediction filters are well known models for signal estimation, in communications, control and many others areas. The classical method for deriving linear prediction coding (LPC) filters is often based on the minimization of a mean square error (MSE). Consequently, second order statistics are only required, but the estimation is only optimal if the residue is independent and identically distributed (iid) Gaussian. In this paper, we derive the ML estimate of the prediction filter. Relationships with robust estimation of auto-regressive (AR) processes, with blind deconvolution and with source separation based on mutual information minimization are then detailed. The algorithm, based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics. Experimental results emphasize on the interest of this approach.

Modeling and Analysis of Some Heavy Tailed Time Series

The thesis has covered various aspects of modeling and analysis of finite mean time series with symmetric stable distributed innovations. Time series analysis based on Box and Jenkins methods are the most popular approaches where the models are linear and errors are Gaussian. We highlighted the limitations of classical time series analysis tools and explored some generalized tools and organized the approach parallel to the classical set up. In the present thesis we mainly studied the estimation and prediction of signal plus noise model. Here we assumed the signal and noise follow some models with symmetric stable innovations.We start the thesis with some motivating examples and application areas of alpha stable time series models. Classical time series analysis and corresponding theories based on finite variance models are extensively discussed in second chapter. We also surveyed the existing theories and methods correspond to infinite variance models in the same chapter. We present a linear filtering method for computing the filter weights assigned to the observation for estimating unobserved signal under general noisy environment in third chapter. Here we consider both the signal and the noise as stationary processes with infinite variance innovations. We derived semi infinite, double infinite and asymmetric signal extraction filters based on minimum dispersion criteria. Finite length filters based on Kalman-Levy filters are developed and identified the pattern of the filter weights. Simulation studies show that the proposed methods are competent enough in signal extraction for processes with infinite variance.Parameter estimation of autoregressive signals observed in a symmetric stable noise environment is discussed in fourth chapter. Here we used higher order Yule-Walker type estimation using auto-covariation function and exemplify the methods by simulation and application to Sea surface temperature data. We increased the number of Yule-Walker equations and proposed a ordinary least square estimate to the autoregressive parameters. Singularity problem of the auto-covariation matrix is addressed and derived a modified version of the Generalized Yule-Walker method using singular value decomposition.In fifth chapter of the thesis we introduced partial covariation function as a tool for stable time series analysis where covariance or partial covariance is ill defined. Asymptotic results of the partial auto-covariation is studied and its application in model identification of stable auto-regressive models are discussed. We generalize the Durbin-Levinson algorithm to include infinite variance models in terms of partial auto-covariation function and introduce a new information criteria for consistent order estimation of stable autoregressive model.In chapter six we explore the application of the techniques discussed in the previous chapter in signal processing. Frequency estimation of sinusoidal signal observed in symmetric stable noisy environment is discussed in this context. Here we introduced a parametric spectrum analysis and frequency estimate using power transfer function. Estimate of the power transfer function is obtained using the modified generalized Yule-Walker approach. Another important problem in statistical signal processing is to identify the number of sinusoidal components in an observed signal. We used a modified version of the proposed information criteria for this purpose.

Metal biosorption onto dry biomass of Arthrospira (Spirulina) platensis and Chlorella vulgaris: Multi-metal systems

Binary and ternary systems of Ni2+, Zn2+, and Pb2+ were investigated at initial metal concentrations of 0.5, 1.0 and 2.0 mM as competitive adsorbates using Arthrospira platensis and Chlorella vulgaris as biosorbents. The experimental results were evaluated in terms of equilibrium sorption capacity and metal removal efficiency and fitted to the multi-component Langmuir and Freundlich isotherms. The pseudo second order model of Ho and McKay described well the adsorption kinetics, and the FT-IR spectroscopy confirmed metal binding to both biomasses. Ni2+ and Zn2+ interference on Pb2+ sorption was lower than the contrary, likely due to biosorbent preference to Pb. In general, the higher the total initial metal concentration, the lower the adsorption capacity. The results of this study demonstrated that dry biomass of C. vulgaris behaved as better biosorbent than A. platensis and suggest its use as an effective alternative sorbent for metal removal from wastewater. (C) 2012 Elsevier B.V. All rights reserved.

Der C 4-Dicarboxylat- und Citratsensor DcuS aus Escherichia coli - Signalerkennung und Regulation

Das Zweikomponentensystem DcuSR aus Escherichia coli reguliert in Abhängigkeit von C4-Dicarboxylaten die Expression der Gene der Fumaratatmung. Die Erkennung von C4-Dicarboxylaten erfolgt über die periplasmatische Domäne der Sensorkinase DcuS und führt zur Autophosphorylierung des konservierten Histidinrestes in der Kinasedomäne. Die Phosphatgruppe wird anschließend auf den Responseregulator DcuR übertragen und führt zur Induktion der Zielgene. Dazu gehören der Antiporter DcuB (dcuB), die anaerobe Fumarase B (fumB) und die Fumaratreduktase (frdABCD). DcuS detektiert neben C4-Dicarboxylaten auch Citrat über die periplasmatische Domäne. In dem nah verwandten Sensor CitA wird Citrat spezifisch über die drei Carboxyl- und die Hydroxylgruppe durch die Bindestellen C1, C2, C3 und H erkannt. DcuS benötigt für die Erkennung von C4-Dicarboxylaten und Citrat die gleichen Bindestellen. Die Citratbindung von DcuS ähnelte der von C4-Dicarboxylaten und unterschied sich von der Citraterkennung in CitA. DcuS konnte durch gerichtete Mutagenese der Bindungsstelle in Varianten überführt werden, die spezifisch für C4-Dicarboxylate (DcuSDC) oder Citrat (DcuSCit) waren. DcuSDC und DcuSCit hatten komplementäre Substratspezifitäten und reagierten entweder auf C4-Dicarboxylate oder auf Citrat (und Mesaconat). Citrat wurde vermutlich als C4-Dicarboxylat (mit einem Acetylrest) und somit über die gleichen Bindestellen wie C4-Dicarboxylate erkannt. Die Bindestellen C2 und C3 sind hoch konserviert und essentiell für die Bindung von zwei Carboxylgruppen von Citrat und C4-Dicarboxylaten. Die Stellen C1 und H werden vermutlich für koordinative Zwecke benötigt. Der Fumarat/Succinat-Antiporter DcuB hat neben der Transportaktivität eine regulatorische Aufgabe im DcuSR-System. Die Deletion von DcuB führte zur konstitutiven Expression der dcuB´-´lacZ Reportergenfusion und anderer DcuSR-regulierter Gene in Abwesenheit von C4-Dicarboxylaten. Die Effektor-unabhängige Expression setzte eine intakte periplasmatische Domäne von DcuS voraus und zeigte in Anwesenheit der spezifischen DcuS-Mutanten (DcuSDC, DcuSCit) eine geänderte Antwort. Die lässt vermuten, dass DcuB die regulatorischen Eigenschaften über eine direkte Wechselwirkung mit DcuS ausübt. Um den phosphorylierten Responseregulator DcuR-P in den Ursprungszustand zurückzuführen, muss dieser dephosphoryliert werden. Die bisher unbekannte Dephosphatase kann dabei entweder von dem Responseregulator, der Sensorkinase oder einem weiteren Protein stammen. DcuR verfügt über eine intrinsische Phosphataseaktivität, die durch den Sensor geringfügig stimuliert wurde.

Method of Detecting System Function by Measuring Frequency Response

Real time battery impedance spectrum is acquired using one time record, Compensated Synchronous Detection (CSD). This parallel method enables battery diagnostics. The excitation current to a test battery is a sum of equal amplitude sin waves of a few frequencies spread over range of interest. The time profile of this signal has duration that is a few periods of the lowest frequency. The voltage response of the battery, average deleted, is the impedance of the battery in the time domain. Since the excitation frequencies are known, synchronous detection processes the time record and each component, both magnitude and phase, is obtained. For compensation, the components, except the one of interest, are reassembled in the time domain. The resulting signal is subtracted from the original signal and the component of interest is synchronously detected. This process is repeated for each component.

Asymptotic optimality of RESTART estimators in highly dependable systems

Abstract We consider a wide class of models that includes the highly reliable Markovian systems (HRMS) often used to represent the evolution of multi-component systems in reliability settings. Repair times and component lifetimes are random variables that follow a general distribution, and the repair service adopts a priority repair rule based on system failure risk. Since crude simulation has proved to be inefficient for highly-dependable systems, the RESTART method is used for the estimation of steady-state unavailability and other reliability measures. In this method, a number of simulation retrials are performed when the process enters regions of the state space where the chance of occurrence of a rare event (e.g., a system failure) is higher. The main difficulty involved in applying this method is finding a suitable function, called the importance function, to define the regions. In this paper we introduce an importance function which, for unbalanced systems, represents a great improvement over the importance function used in previous papers. We also demonstrate the asymptotic optimality of RESTART estimators in these models. Several examples are presented to show the effectiveness of the new approach, and probabilities up to the order of 10-42 are accurately estimated with little computational effort.

Training and search methods for speech recognition.

Speech recognition involves three processes: extraction of acoustic indices from the speech signal, estimation of the probability that the observed index string was caused by a hypothesized utterance segment, and determination of the recognized utterance via a search among hypothesized alternatives. This paper is not concerned with the first process. Estimation of the probability of an index string involves a model of index production by any given utterance segment (e.g., a word). Hidden Markov models (HMMs) are used for this purpose [Makhoul, J. & Schwartz, R. (1995) Proc. Natl. Acad. Sci. USA 92, 9956-9963]. Their parameters are state transition probabilities and output probability distributions associated with the transitions. The Baum algorithm that obtains the values of these parameters from speech data via their successive reestimation will be described in this paper. The recognizer wishes to find the most probable utterance that could have caused the observed acoustic index string. That probability is the product of two factors: the probability that the utterance will produce the string and the probability that the speaker will wish to produce the utterance (the language model probability). Even if the vocabulary size is moderate, it is impossible to search for the utterance exhaustively. One practical algorithm is described [Viterbi, A. J. (1967) IEEE Trans. Inf. Theory IT-13, 260-267] that, given the index string, has a high likelihood of finding the most probable utterance.

STAT3 activation by cytokines utilizing gp130 and related transducers involves a secondary modification requiring an H7-sensitive kinase.

Ciliary neurotrophic factor, oncostatin M, leukemia-inhibitory factor, and interleukin 6 are related cytokines that initiate signaling by homodimerizing the signal-transducing receptor component gp130 or by heterodimerizing gp130 with a gp130-related receptor component. Receptor dimerization in turn activates receptor-associated kinases of the Jak/Tyk family, resulting in the rapid tyrosine phosphorylation of several intracellular proteins, including those of two members of the signal transducers and activators of transcription (STAT) family--STAT1 and STAT3. Here we show that all cytokines that utilize gp130 sequentially induce two distinct forms of STAT3 in all responding cells examined, with the two forms apparently differing because of a time-dependent secondary serine/threonine phosphorylation involving an H7-sensitive kinase. While both STAT3 forms bind DNA and translocate to the nucleus, the striking time-dependent progression from one form to the other implies other important functional differences between the two forms. Granulocyte colony-stimulating factor, which utilizes a receptor highly related to gp130, also induces these two forms of STAT3. In contrast to a number of other cytokines and growth factors, all cytokines using gp130 and related signal transducers consistently and preferentially induce the two forms of STAT3 as compared with STAT1; this characteristic STAT activation pattern is seen regardless of which Jak/Tyk kinases are used in a particular response, consistent with the notion that the receptor components themselves are the primary determinants of which STATs are activated.

Novel three-component blends based on poly(L-lactide)

A significant number of poly a-ester homologues of poly(L-lactide) (PLLA) have been synthesized and used in miscibility studies together with conventional isomeric diacid-diol polyester variants, poly ß-esters (based on ß-hydroxybutyrate (HB) and ß-hydroxyvalerate (HV)), poly e-caprolactone (PCL), poly e-caprolactone copolymers (e.g. poly(L-lactide-co-caprolactone), and a series of cellulose-based polymers (e.g. cellulose acetate butyrate (CAB), cellulose acetate propionate (CAP)). A combinatorial approach to rapid miscibility screening using 96-well plates and a uv-visible multi-wavelength plate reader has been developed enabling the clarity of PLLA-based multi-component blend films to be observed. Using these techniques and materials, the ternary phase compatibility diagrams of a range of three-component blend films was prepared, illustrating ranges of behavior varying from miscible blends giving rise to clear films to immiscible blends which are opaque. In this way, novel three-component blends of PLLA/CAB/PCL were developed which are miscible when the CAB content is more than 30%, PLLA less than 80% and PCL less than 60%.

Multi-impurity adsorption model for modeling crystal purity and shape evolution during crystallization processes in impure media

Peer reviewed