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Copulas have already proven their flexibility in rainfall modelling. Yet, their use is generally restricted to the description of bivariate dependence. Recently, vine copulas have been introduced, allowing multi-dimensional dependence structures to be described on the basis of a stage by stage mixing of two-dimensional copulas. This paper explores the use of such vine copulas in order to incorporate all relevant dependencies between the storm variables of interest. On the basis of such fitted vine copulas, an external storm structure is modeled. An internal storm structure is superimposed based on Huff curves, such that a continuous time series of rainfall is generated. The performance of the rainfall model is evaluated through a statistical comparison between an ensemble of synthetical rainfall series and the observed rainfall series and through the comparison of the annual maxima.

Gibberellic acid is a plant growth hormone that promotes cell expansion and division. Studies have aimed at optimizing and reducing production costs, which could make its application economically viable for different cultivars. Gibberellins consist of a large family of plant growth hormones discovered in the 1930s, which are synthesized via the terpenes route from the geranylgeranyl diphosphate and feature a basic structure formed by an ent-gibberellane tetracyclic skeleton. Among them, only four have biological activity, including gibberellic acid (GA

Aim: Zirconium-89 has gained great interest for PET, when imaging at late time points is required. Desferrioxamine B (DFO), is mostly used for this radionuclide as bifunctional chelator (BFC) and w ...

Of all natural disasters, the economic and environmental consequences of droughts are among the highest because of their longevity and widespread spatial extent. Because of their extreme behaviour, studying droughts generally requires long time series of historical climate data. Rainfall is a very important variable for calculating drought statistics, for quantifying historical droughts or for assessing the impact on other hydrological (e.g. water stage in rivers) or agricultural (e.g. irrigation requirements) variables. Unfortunately, time series of historical observations are often too short for such assessments. To circumvent this, one may rely on the synthetic rainfall time series from stochastic point process rainfall models, such as Bartlett–Lewis models. The present study investigates whether drought statistics are preserved when simulating rainfall with Bartlett–Lewis models. Therefore, a 105 yr 10 min rainfall time series obtained at Uccle, Belgium is used as a test case. First, drought events were identified on the basis of the Effective Drought Index (EDI), and each event was characterized by two variables, i.e. drought duration (D) and drought severity (S). As both parameters are interdependent, a multivariate distribution function, which makes use of a copula, was fitted. Based on the copula, four types of drought return periods are calculated for observed as well as simulated droughts and are used to evaluate the ability of the rainfall models to simulate drought events with the appropriate characteristics. Overall, all Bartlett–Lewis model types studied fail to preserve extreme drought statistics, which is attributed to the model structure and to the model stationarity caused by maintaining the same parameter set during the whole simulation period.

Most of the hydrological and hydraulic studies refer to the notion of a return period to quantify design variables. When dealing with multiple design variables, the well-known univariate statistical analysis is no longer satisfactory, and several issues challenge the practitioner. How should one incorporate the dependence between variables? How should a multivariate return period be defined and applied in order to yield a proper design event? In this study an overview of the state of the art for estimating multivariate design events is given and the different approaches are compared. The construction of multivariate distribution functions is done through the use of copulas, given their practicality in multivariate frequency analyses and their ability to model numerous types of dependence structures in a flexible way. A synthetic case study is used to generate a large data set of simulated discharges that is used for illustrating the effect of different modelling choices on the design events. Based on different uni- and multivariate approaches, the design hydrograph characteristics of a 3-D phenomenon composed of annual maximum peak discharge, its volume, and duration are derived. These approaches are based on regression analysis, bivariate conditional distributions, bivariate joint distributions and Kendall distribution functions, highlighting theoretical and practical issues of multivariate frequency analysis. Also an ensemble-based approach is presented. For a given design return period, the approach chosen clearly affects the calculated design event, and much attention should be given to the choice of the approach used as this depends on the real-world problem at hand.

Analyses of randomised experiments frequently include attempts to decompose the intention-to-treat effect into a direct and indirect effect, mediated by given intermediaries, with the aim to shed light onto the treatment mechanism. Methods from causal mediation analysis have facilitated this by allowing for arbitrary models for the outcome and the mediator. They thereby generalise the traditional approach to direct and indirect effects, which is essentially limited to linear models. The default maximum likelihood methods make use of a model for the conditional distribution of the mediator, given treatment and baseline covariates, but are prone to bias when that model is misspecified. In randomised experiments, specification of such model can be easily avoided, but at the expense of a sometimes major efficiency loss when those baseline covariates are predictive of the mediator. In this article, we develop a compromise approach: it makes use of a model for the mediator to optimally extract information from the baseline covariate data but is insulated from the impact of misspecification of that model; it achieves this by exploiting the known randomisation probabilities. Simulation studies and the analysis of a randomised study show major efficiency gains and confirm our theoretical findings that the default methods from causal mediation analysis are sometimes, although not always, reasonably robust to model misspecification. Copyright © 2017 John WileySons, Ltd.

Volatile compounds with fruity characteristics were produced by Ceratocystis fimbriata in two different bioreactors: columns (laboratory scale) and horizontal drum (semi-pilot scale). Coffee husk was used as substrate for the production of volatile compounds by solid-state fermentation. The production of volatile compounds was significantly higher when horizontal drum bioreactor was used than when column bioreactors were used. These results showed that this model of bioreactor presents good perspectives for scale-up and application in an industrial production. Headspace analysis of the solid-state culture detected twelve compounds, among them: ethanol, acetaldehyde, ethyl acetate, ethyl propionate, and isoamyl acetate. Ethyl acetate was the predominant product in the headspace (28.55 µmol/L/g of initial dry matter). Activated carbon, Tenax-TA, and Amberlite XAD-2 were tested to perform the recovery of the compounds. The adsorbent columns were connected to the column-type bioreactor. All compounds present in the headspace of the columns were adsorbed in Amberlite XAD-2. With Tenax-TA, acetaldehyde was adsorbed in higher concentrations. However, the recovery found by using the activated carbon was very low.

In this paper, a method for analysis and modeling of coplanartransmission interconnect lines that are placed on top ofsilicon-silicon oxide substrates is presented. The potential functionis expressed by series expansions in terms of solutions of the Laplaceequation for each homogeneous region of layered structure. Theexpansion coefficients of different series are related to each otherand to potentials applied to the conductors via boundary conditions. Inthe plane of conductors, boundary conditions are satisfied at Nddiscrete points with Nd being equal to the number of terms in theseries expansions. The resulting system of inhomogeneous linearequations is solved by matrix inversion. No iterations are required. Adiscussion of the calculated line admittance parameters as functions ofwidth of conductors, thickness of the layers, and frequency is given.The interconnect capacitance and conductance per unit length resultsare given and compared with those obtained using full wave solutions,and good agreement have been obtained in all the cases treated.

Of all natural disasters, the economic and environmental consequences of droughts are among the highest because of their longevity and widespread spatial extent. Because of their extreme behaviour, studying droughts generally requires long time series of historical climate data. Rainfall is a very important variable for calculating drought statistics, for quantifying historical droughts or for assessing the impact on other hydrological (e.g. water stage in rivers) or agricultural (e.g. irrigation requirements) variables. Unfortunately, time series of historical observations are often too short for such assessments. To circumvent this, one may rely on the synthetic rainfall time series from stochastic point process rainfall models, such as Bartlett–Lewis models. The present study investigates whether drought statistics are preserved when simulating rainfall with Bartlett–Lewis models. Therefore, a 105 yr 10 min rainfall time series obtained at Uccle, Belgium is used as test case. First, drought events were identified on the basis of the Effective Drought Index (EDI), and each event was characterized by two variables, i.e. drought duration (D) and drought severity (S). As both parameters are interdependent, a multivariate distribution function, which makes use of a copula, was fitted. Based on the copula, four types of drought return periods are calculated for observed as well as simulated droughts and are used to evaluate the ability of the rainfall models to simulate drought events with the appropriate characteristics. Overall, all Bartlett–Lewis type of models studied fail in preserving extreme drought statistics, which is attributed to the model structure and to the model stationarity caused by maintaining the same parameter set during the whole simulation period.

BACKGROUND AND PURPOSE: Conventional platinum coils cause imaging artifacts that reduce imaging quality and therefore impair imaging interpretation on intraprocedural or noninvasive follow-up imaging. The purpose of this study was to evaluate imaging characteristics and artifact production of polymeric coils compared with standard platinum coils in vitro and in vivo. MATERIALS AND METHODS: Polymeric coils and standard platinum coils were evaluated in vitro with the use of 2 identical silicon aneurysm models coiled with a packing attenuation of 20% each. DSA, flat panel CT, CT, and MR imaging were performed. In vivo evaluation of imaging characteristics of polymeric coils was performed in experimentally created rabbit carotid bifurcation aneurysms. DSA, CT/CTA, and MR imaging were performed after endovascular treatment of the aneurysms. Images were evaluated regarding visibility of individual coils, coil mass, artifact production, and visibility of residual flow within the aneurysm. RESULTS: Overall, in vitro and in vivo imaging showed relevantly reduced artifact production of polymeric coils in all imaging modalities compared with standard platinum coils. Image quality of CT and MR imaging was improved with the use of polymeric coils, which permitted enhanced depiction of individual coil loops and residual aneurysm lumen as well as the peri-aneurysmal area. Remarkably, CT images demonstrated considerably improved image quality with only minor artifacts compared with standard coils. On DSA, polymeric coils showed transparency and allowed visualization of superimposed vessel structures. CONCLUSIONS: This initial experimental study showed improved imaging quality with the use of polymeric coils compared with standard platinum coils in all imaging modalities. This might be advantageous for improved intraprocedural imaging for the detection of complications and posttreatment noninvasive follow-up imaging.

Most of the hydrological and hydraulic studies refer to the notion of a return period to quantify design variables. When dealing with multiple design variables, the well-known univariate statistical analysis is no longer satisfactory and several issues challenge the practitioner. How should one incorporate the dependence between variables? How should the joint return period be defined and applied? In this study, an overview of the state-of-the-art for defining joint return periods is given. The construction of multivariate distribution functions is done through the use of copulas, given their practicality in multivariate frequency analysis and their ability to model numerous types of dependence structures in a flexible way. A case study focusing on the selection of design hydrograph characteristics is presented and the design values of a three-dimensional phenomenon composed of peak discharge, volume and duration are derived. Joint return period methods based on regression analysis, bivariate conditional distributions, bivariate joint distributions, and Kendal distribution functions are investigated and compared highlighting theoretical and practical issues of multivariate frequency analysis. Also an ensemble-based method is introduced. For a given design return period, the method chosen clearly affects the calculated design event. Eventually, light is shed on the practical implications of a chosen method.

The use of rainfall time series for various applications is widespread. However, in many cases historical rainfall records lack in length or quality for certain practical purposes, resulting in a reliance on rainfall models to supply simulated rainfall time series, e.g., in the design of hydraulic structures. One way to obtain such simulations is by means of stochastic point process rainfall models, such as the Bartlett-Lewis type of model. It is widely acknowledged that the calibration of such models suffers from the presence of multiple local minima which local search algorithms usually fail to avoid. To meet this shortcoming, four relatively new global optimization methods are presented and tested for their abilities to calibrate the Modified Bartlett-Lewis Model (MBL). The list of tested methods consists of: the Downhill Simplex Method (DSM), Simplex-Simulated Annealing (SIMPSA), Particle Swarm Optimization (PSO) and Shuffled Complex Evolution (SCE-UA). The parameters of these algorithms are first optimized to ensure optimal performance, after which they are used for calibration of the MBL model. Furthermore, this paper addresses the issue of subjectivity in the choice of weights in the objective function. Three alternative weighing methods are compared to determine whether or not simulation results (obtained after calibration with the best optimization method) are influenced by the choice of weights.

[1] Because of a lack of historical rainfall time series of considerable length, one often has to rely on simulated rainfall time series, e.g., in the design of hydraulic structures. One way to simulate such time series is by means of stochastic point process rainfall models, such as the Bartlett-Lewis type of model. For the evaluation of model performance, with a focus on the reproduction of extreme rainfall events, often a univariate extreme value analysis is performed. Recently developed concepts in statistical hydrology now offer other means of evaluating the overall performance of such models. In this study, a copula-based frequency analysis of storms is proposed as a tool to evaluate differences between the return periods of several types of observed and modeled storms. First, this study performs an analysis of several storm variables, which indicates a problem with the modeling of the temporal structure of rainfall by the models. Thereafter, the bivariate frequency analysis of storms, defined by their duration and volume, illustrates the underestimation and overestimation of the return period of the storms simulated by the models, which is partially explained by a large difference in the marginal distribution functions of the storm duration and storm volume, the difference in the degree of association between the latter, and a different mean storm interarrival time. The proposed methodology allows for the identification of some problems with the rainfall simulations from which recommendations for possible improvements to rainfall models can be made.

Fine-scale rainfall data is important for many hydrological applications. However, often the only data available is at a coarse scale. To bridge this gap in resolution, stochastic disaggregation methods can be used. Such methods generally assume that the distribution of the field is stationary, i.e. the distribution for the entire (fine-scale) field is the same as the distribution of a smaller region within the field. This assumption is generally incorrect and we provide the proof of concept of a method to estimate the distribution of a smaller region. In this method, a copula is used to construct a bivariate distribution describing the relation between the scales. This distribution is then used to estimate the distribution of the fine-scale rainfall within a single coarse-scale pixel, by conditioning on the coarse-scale rainfall depth.

In order to determine the clinical benefit of positron emission tomography (PET) for dose delivery verification in proton therapy, we performed a patient case study comparing in-situ with in-room time-of-flight (TOF) PET. For the in-situ option, we consider both a (limited-angle) clinical scanner and a dual-head scanner placed close to the patient.

The use of design storms can be very useful in many hydrological and hydraulic practices. In this study, the concept of a copula-based secondary return period in combination with the concept of mass curves is used to generate point-scale design storms. The analysis is based on storms selected from the 105 year rainfall time series with a 10 min resolution, measured at Uccle, Belgium. In first instance, bivariate copulas and secondary return periods are explained, together with a focus on which couple of storm variables is of highest interest for the analysis and a discussion of how the results might be affected by the goodness-of-fit of the copula. Subsequently, the fitted copula is used to sample storms with a predefined secondary return period for which characteristic variables such as storm duration and total storm depth can be derived. In order to construct design storms with a realistic storm structure, mass curves of 1st, 2nd, 3rd and 4th quartile storms are developed. An analysis shows that the assumption of independence between the secondary return period and the internal storm structure could be made. Based on the mass curves, a technique is developed to randomly generate an intrastorm structure. The coupling of both techniques eventually results in a methodology for stochastic design storm generation. Finally, its practical usefulness for design studies is illustrated based on the generation of a set of statistically identical design storm and rainfall-runoff modelling.

Enzymes are special proteins, which catalyze chemical reactions with great specificity and rate enhancements. These reactions are the basis of the metabolism of all living organisms, and provide tremendous and economical biocatalyst conversions (Godfrey & West 1996). First half of the last century saw a rapid development in enzyme chemistry. Commercial exploitation of microbial enzymes began much before their nature and properties were worked out. For centuries, extracts of plants had been used to bring about hydrolysis of polymeric materials. However, these sources of enzymes were unreliable and expensive too, hence search for alternative sources began. Largely, this was found in the microbial cultures (Menon & Rao 1999). The first enzyme produced industrially, as the fungal amylase, was amylase takadiastase, employed as a pharmaceutical agent (for digestive disorders) in the United States in 1894. Otto Roehm’s patented “laundry process for any and all clothing via trypic enzyme additives” was announced in 1915. Later on, more researches focused on discovering the primary, secondary and tertiary structures of enzyme polypeptides, as well as the mechanism of enzyme action. The Enzyme Commission, set up by the International Union of Biochemists (1965), has published a system of enzyme classification, which is universally adhered to throughout biochemistry (Menon & Rao 1999). Although about 25,000 natural enzymes are speculated to exist, only about 2,100 have been recognized by the International Union of Biochemists. This means about 90% of the reservoir of biocatalysts still remains to be discovered and characterized.

U svijetu postoji velika potražnja za limunskom kiselinom zbog njezine male toksicnosti u usporedbi s ostalim regulatorima kiselosti koji se primijenjuju u farmaceutskoj i prehrambenoj industriji. Limunska se kiselina dodaje i detergentima, sredstvima za cišcenje, kozmetickim preparatima te higijenskim i ostalim proizvodima. Svjetska proizvodnja dosegla je 1,4 milijuna tona, a potražnja odnosno potrošnja limunske kiseline raste 3,5-4 % na godinu. Zbog rastuce potražnje na tržištu, opstali su samo veliki proizvodaci. Povecanje proizvodnje limunske kiseline osobito je važno pa je potrebno razmotriti sve nacine da bi se to postiglo. Danas još uvijek prevladava proizvodnja submerznim postupkom, a proizvodnja na cvrstoj podlozi otvara proizvodacima nove mogucnosti. Mnogi nusproizvodi u poljoprivredi mogu se upotrijebiti za proizvodnju limunske kiseline pa se time smanjenju troškovi proizvodnje. Uporaba jeftinijih supstrata za bioproces od ekonomske je i ekološke važnosti. Povecana proizvodnja limunske kiseline može se postici i primjenom sojeva poboljšanih mutagenezom i selekcijom., There is a great worldwide demand for citric acid consumption due to its low toxicity when compared with other acidulants used mainly in the pharmaceutical and food industries. Other applications of citric acid can be found in detergents and cleaning products, cosmetics and toiletries, and other. Global production has now reached 1.4 million tonnes and there is annual growth of 3.5–4.0 % in demand/consumption of citric acid. As a result of the adverse market conditions, only big producers have survived. Any increase in citric acid productivity would be of potential interest and hence there is an obvious need to consider all possible ways in which this might be achieved. The production by submerged fermentation is still dominating. However, solid-state processes can create new possibilities for producers. Many by-products and residues of the agro-industry can be used in the production of citric acid. A cost reduction in citric acid production can be achieved by using less expensive substrates. The use of agro-industrial residues as support in solid-state fermentation is economically important and minimizes environmental problems. Other perspectives for citric acid production sector are the improvement of citric acid producing strains, which have been carried out by mutagenesis and selection.

Volatile compounds with fruity characteristics were produced by Ceratocystis fimbriata in two different bioreactors: columns (laboratory scale) and horizontal drum (semi-pilot scale). Coffee husk was used as substrate for the production of volatile compounds by solid-state fermentation. The production of volatile compounds was significantly higher when horizontal drum bioreactor was used than when column bioreactors were used. These results showed that this model of bioreactor presents good perspectives for scale-up and application in an industrial production. Headspace analysis of the solid-state culture detected twelve compounds, among them: ethanol, acetaldehyde, ethyl acetate, ethyl propionate, and isoamyl acetate. Ethyl acetate was the predominant product in the headspace (28.55 µmol/L/g of initial dry matter). Activated carbon, Tenax-TA, and Amberlite XAD-2 were tested to perform the recovery of the compounds. The adsorbent columns were connected to the column-type bioreactor. All compounds present in the headspace of the columns were adsorbed in Amberlite XAD-2. With Tenax-TA, acetaldehyde was adsorbed in higher concentrations. However, the recovery found by using the activated carbon was very low., Hlapljivi spojevi s voćnom aromom dobiveni su s pomoću plijesni Ceratosystis fimbriata u dva različita bioreaktora, i to u kolonskom bioreaktoru (u laboratoriju) i horizontalnom bubnju (poluindustrijski). Kao čvrsti supstrat za fermentaciju upotrijebljena je lupina kave. Proizvodnja hlapljivih spojeva bila je kudikamo veća u horizontalnom bubanjskom reaktoru. Stoga ovaj model bioreaktora ima sve preduvjete za uvećanje i primjenu u industrijskoj proizvodnji. Kromatografskom analizom plinske faze iznad fermentiranog supstrata prona|eno je 12 hlapljivih spojeva, a među njima etanol, acetaldehid, etilni acetat, etilni propionat i izoamilni acetat. Etilni acetat bio je glavni hlapljivi proizvod u plinskoj fazi (28,55 µmol/L/g početne suhe tvari). Za izdvajanje hlapljivih spojeva ispitani su aktivni ugljen, Tenax-TA i Amberlite XAD-2. Kolone za adsorpciju bile su povezane s kolonskim bioreaktorom. Sve hlapljive spojeve iz plinskog prostora bioreaktora adsorbirao je Amberlite XAD-2. Tenax-TA adsorbirao je više acetaldehida, a izdvajanje hlapljivih spojeva na aktivnom ugljenu bilo je vrlo slabo.

Industrial and environmental biotechnology are going to new paths, resulting in processes with "clean technologies", with the maximum production and the less residues. Technologies of remediation and bioremediation are continuously being improved using genetically modified microorganisms or those naturally occurring, to clean residues and contaminated areas from toxic organics. Bioremediation of soils, water and marine environments has many advantages but at the same time it is a challenge for the researchers and engineers. Consequently, it is extremely important to carry out feasibility study based on pilot-testing before starting a remediation project in order to determine the best conditions for the process. The article presents a brief review of bioremediation including the description of the different methods applied to soil and industrial wastes, and, finally, some experiences of solid-state fermentation in relation to bioremediation.

Several simulations of SPECT neuroactivation studies have been performed in order to determine the influence of both study size and activation focus characteristics on the detection of brain activation foci following a pixel-based statistical analysis. This was achieved by developing a methodology based on the Hoffman software brain phantom, SPECT acquisition simulation software, standard reconstruction software, and the Statistical Parametric Mapping (SPM96) package. We present results on the minimal activation levels required for focus detection. Furthermore, the improved sensitivity of the analysis resulting from the use of an iterative reconstruction technique (OSEM) with regard to the classical filtered backprojection (FBP) is assessed quantitatively, and the various physical, processing, and physiological parameters that potentially influence the detection of foci are discussed. Finally, the influence is investigated of the height threshold as implemented in SPM96 upon the size of the detected foci. Practical guidelines are proposed with regard to the number of subjects per group for SPECT activation studies following the split-dose design.