Benchmark problems for reactive transport modeling of the generation and attenuation of acid rock drainage

Acid rock drainage (ARD) is a problem of international relevance with substantial environmental and economic implications. Reactive transport modeling has proven a powerful tool for the process-based assessment of metal release and attenuation at ARD sites. Although a variety of models has been used to investigate ARD, a systematic model intercomparison has not been conducted to date. This contribution presents such a model intercomparison involving three synthetic benchmark problems designed to evaluate model results for the most relevant processes at ARD sites. The first benchmark (ARD-B1) focuses on the oxidation of sulfide minerals in an unsaturated tailing impoundment, affected by the ingress of atmospheric oxygen. ARD-B2 extends the first problem to include pH buffering by primary mineral dissolution and secondary mineral precipitation. The third problem (ARD-B3) in addition considers the kinetic and pH-dependent dissolution of silicate minerals under low pH conditions. The set of benchmarks was solved by four reactive transport codes, namely CrunchFlow, Flotran, HP1, and MIN3P. The results comparison focused on spatial profiles of dissolved concentrations, pH and pE, pore gas composition, and mineral assemblages. In addition, results of transient profiles for selected elements and cumulative mass loadings were considered in the intercomparison. Despite substantial differences in model formulations, very good agreement was obtained between the various codes. Residual deviations between the results are analyzed and discussed in terms of their implications for capturing system evolution and long-term mass loading predictions.

Automatic multi-resolution shape modeling of multi-organ structures.

Point Distribution Models (PDM) are among the most popular shape description techniques and their usefulness has been demonstrated in a wide variety of medical imaging applications. However, to adequately characterize the underlying modeled population it is essential to have a representative number of training samples, which is not always possible. This problem is especially relevant as the complexity of the modeled structure increases, being the modeling of ensembles of multiple 3D organs one of the most challenging cases. In this paper, we introduce a new GEneralized Multi-resolution PDM (GEM-PDM) in the context of multi-organ analysis able to efficiently characterize the different inter-object relations, as well as the particular locality of each object separately. Importantly, unlike previous approaches, the configuration of the algorithm is automated thanks to a new agglomerative landmark clustering method proposed here, which equally allows us to identify smaller anatomically significant regions within organs. The significant advantage of the GEM-PDM method over two previous approaches (PDM and hierarchical PDM) in terms of shape modeling accuracy and robustness to noise, has been successfully verified for two different databases of sets of multiple organs: six subcortical brain structures, and seven abdominal organs. Finally, we propose the integration of the new shape modeling framework into an active shape-model-based segmentation algorithm. The resulting algorithm, named GEMA, provides a better overall performance than the two classical approaches tested, ASM, and hierarchical ASM, when applied to the segmentation of 3D brain MRI.

Atomistic Modeling of Effect of Mg on Oxygen Vacancy Diffusion in α-Alumina

Oxygen diffusion plays an important role in grain growth and densification during the sintering of alumina ceramics and governs high-temperature processes such as creep. The atomistic mechanism for oxygen diffusion in alumina is, however, still debated; atomistic calculations not being able to match experimentally determined activation energies for oxygen vacancy diffusion. These calculations are, however, usually performed for perfectly pure crystals, whereas virtually every experimental alumina sample contains a significant fraction of impurity/dopants ions. In this study, we use atomistic defect cluster and nudged elastic band (NEB) calculations to model the effect of Mg impurities/dopants on defect binding energies and migration barriers. We find that oxygen vacancies can form energetically favorable clusters with Mg, which reduces the number of mobile species and leads to an additional 1.5 eV energy barrier for the detachment of a single vacancy from Mg. The migration barriers of diffusive jumps change such that an enhanced concentration of oxygen vacancies is expected around Mg ions. Mg impurities were also found to cause destabilization of certain vacancy configurations as well as enhanced vacancy–vacancy interaction.

3D-modeling of Mercury's solar wind sputtered surface-exosphere environment

The efficiency of sputtered refractory elements by H+ and He++ solar wind ions from Mercury's surface and their contribution to the exosphere are studied for various solar wind conditions. A 3D solar wind-planetary interaction hybrid model is used for the evaluation of precipitation maps of the sputter agents on Mercury's surface. By assuming a global mineralogical surface composition, the related sputter yields are calculated by means of the 2013 SRIM code and are coupled with a 3D exosphere model. Because of Mercury's magnetic field, for quiet and nominal solar wind conditions the plasma can only precipitate around the polar areas, while for extreme solar events (fast solar wind, coronal mass ejections, interplanetary magnetic clouds) the solar wind plasma has access to the entire dayside. In that case the release of particles form the planet's surface can result in an exosphere density increase of more than one order of magnitude. The corresponding escape rates are also about an order of magnitude higher. Moreover, the amount of He++ ions in the precipitating solar plasma flow enhances also the release of sputtered elements from the surface in the exosphere. A comparison of our model results with MESSENGER observations of sputtered Mg and Ca elements in the exosphere shows a reasonable quantitative agreement. (C) 2015 Elsevier Ltd. All rights reserved.

The Devil’s Calculus: Mathematical Models of Civil War

In spite of the movement to turn political science into a real science, various mathematical methods that are now the staples of physics, biology, and even economics are thoroughly uncommon in political science, especially the study of civil war. This study seeks to apply such methods - specifically, ordinary differential equations (ODEs) - to model civil war based on what one might dub the capabilities school of thought, which roughly states that civil wars end only when one side’s ability to make war falls far enough to make peace truly attractive. I construct several different ODE-based models and then test them all to see which best predicts the instantaneous capabilities of both sides of the Sri Lankan civil war in the period from 1990 to 1994 given parameters and initial conditions. The model that the tests declare most accurate gives very accurate predictions of state military capabilities and reasonable short term predictions of cumulative deaths. Analysis of the model reveals the scale of the importance of rebel finances to the sustainability of insurgency, most notably that the number of troops required to put down the Tamil Tigers is reduced by nearly a full order of magnitude when Tiger foreign funding is stopped. The study thus demonstrates that accurate foresight may come of relatively simple dynamical models, and implies the great potential of advanced and currently unconventional non-statistical mathematical methods in political science.

Bayesian joint modeling of longitudinal and survival data

The joint modeling of longitudinal and survival data is a new approach to many applications such as HIV, cancer vaccine trials and quality of life studies. There are recent developments of the methodologies with respect to each of the components of the joint model as well as statistical processes that link them together. Among these, second order polynomial random effect models and linear mixed effects models are the most commonly used for the longitudinal trajectory function. In this study, we first relax the parametric constraints for polynomial random effect models by using Dirichlet process priors, then three longitudinal markers rather than only one marker are considered in one joint model. Second, we use a linear mixed effect model for the longitudinal process in a joint model analyzing the three markers. In this research these methods were applied to the Primary Biliary Cirrhosis sequential data, which were collected from a clinical trial of primary biliary cirrhosis (PBC) of the liver. This trial was conducted between 1974 and 1984 at the Mayo Clinic. The effects of three longitudinal markers (1) Total Serum Bilirubin, (2) Serum Albumin and (3) Serum Glutamic-Oxaloacetic transaminase (SGOT) on patients' survival were investigated. Proportion of treatment effect will also be studied using the proposed joint modeling approaches. ^ Based on the results, we conclude that the proposed modeling approaches yield better fit to the data and give less biased parameter estimates for these trajectory functions than previous methods. Model fit is also improved after considering three longitudinal markers instead of one marker only. The results from analysis of proportion of treatment effects from these joint models indicate same conclusion as that from the final model of Fleming and Harrington (1991), which is Bilirubin and Albumin together has stronger impact in predicting patients' survival and as a surrogate endpoints for treatment. ^

Preclinical modeling of multi-drug cancer therapies

Anticancer drugs typically are administered in the clinic in the form of mixtures, sometimes called combinations. Only in rare cases, however, are mixtures approved as drugs. Rather, research on mixtures tends to occur after single drugs have been approved. The goal of this research project was to develop modeling approaches that would encourage rational preclinical mixture design. To this end, a series of models were developed. First, several QSAR classification models were constructed to predict the cytotoxicity, oral clearance, and acute systemic toxicity of drugs. The QSAR models were applied to a set of over 115,000 natural compounds in order to identify promising ones for testing in mixtures. Second, an improved method was developed to assess synergistic, antagonistic, and additive effects between drugs in a mixture. This method, dubbed the MixLow method, is similar to the Median-Effect method, the de facto standard for assessing drug interactions. The primary difference between the two is that the MixLow method uses a nonlinear mixed-effects model to estimate parameters of concentration-effect curves, rather than an ordinary least squares procedure. Parameter estimators produced by the MixLow method were more precise than those produced by the Median-Effect Method, and coverage of Loewe index confidence intervals was superior. Third, a model was developed to predict drug interactions based on scores obtained from virtual docking experiments. This represents a novel approach for modeling drug mixtures and was more useful for the data modeled here than competing approaches. The model was applied to cytotoxicity data for 45 mixtures, each composed of up to 10 selected drugs. One drug, doxorubicin, was a standard chemotherapy agent and the others were well-known natural compounds including curcumin, EGCG, quercetin, and rhein. Predictions of synergism/antagonism were made for all possible fixed-ratio mixtures, cytotoxicities of the 10 best-scoring mixtures were tested, and drug interactions were assessed. Predicted and observed responses were highly correlated (r2 = 0.83). Results suggested that some mixtures allowed up to an 11-fold reduction of doxorubicin concentrations without sacrificing efficacy. Taken together, the models developed in this project present a general approach to rational design of mixtures during preclinical drug development. ^

Proceedings of the Nineteenth Annual Biochemical Engineering Symposium

The nineteenth symposium was held at the University of Missouri–Columbia on April 22, 1989. A total of eighteen papers were scheduled for presentation, of which nine were in poster session. Finally, fifteen papers were presented and sixteen were submitted for this proceedings. It was attended by 53 participants from five institutions. A sixth group (from Colorado State University) was kept from attending the symposium due to mechanical problems on the road and we missed them. Since they worked hard at their presentations, I requested CSU-group to submit their papers for the proceedings and I am happy that they did. ContentsMathematical modelling of a flour milling system. K. Takahashi, Y. Chen, J. Hosokoschi, and L. T. Fan. Kansas State University A novel solution to the problem of plasmid segregation in continuous bacterial fermentations. K.L. Henry, R. H. Davis, and A. L. Taylor. University of Colorado Modelling of embryonic growth in avian and reptile Eggs. C.L. Krause, R. C. Seagrave, and R. A. Ackerman. Iowa State University Mathematical modeling of in situ biodegradation processes. J.C. Wu, L. T. Fan, and L. E. Erickson. Kansas State University Effect of molecular changes on starch viscosity. C.H. Rosane and V. G. Murphy. Colorado State University Analysis of two stage recombinant bacterial fermentations using a structured kinetic model. F. Miao and D. S. Kampala. University of Colorado Lactic acid fermentation from enzyme-thinned starch by Lactobacillus amylovorus. P.S. Cheng, E. L. Iannotti, R. K. Bajpai, R. Mueller, and s. Yaeger. University of Missouri–Columbia Solubilization of preoxidized Texas lignite by cell-free broths of Penicillium strains. R. Moolick, M. N. Karim, J. C. Linden, and B. L. Burback. Colorado State University Separation of proteins from polyelectrolytes by ultrafiltration. A.G. Bazzano and C. E. Glatz. Iowa State University Growth estimation and modelling of Rhizopus oligosporus in solid state fermentations. D.-H. Ryoo, V. G. Murphy, M. N. Karim, and R. P. Tengerdy. Colorado State University Simulation of ethanol fermentations from sugars in cheese whey. C.J. Wang and R. K. Bajpai. University of Missouri–Columbia Studies on protoplast fusion of B. licheniformis. B. Shi, Kansas State University Cell separations of non-dividing and dividing yeasts using an inclined settler. C.-Y. Lee, R. H. Davis, and R. A. Sclafani. University of Colorado Effect of·serum upon local hydrodynamics within an airlift column. G.T. Jones, L. E. Erickson, and L. A. Glasgow. Kansas State University Optimization of heterologous protein secretion in continuous culture. A. Chatterjee, W. F. Remirez, and R. H. Davis. University of Colorado An improved model for lactic acid fermentation. P. Yeh, R. K. Bajpai, and E. L. Iannotti. University of Missouri–Columbia

Proceedings of the Twentieth Annual Biochemical Engineering Symposium

The 20th Annual Biochemical Engineering Symposium was held at Kansas State University on April 21,1990. The objectives of the symposium were to provide: (i) a forum for informal discussion of biochemical engineering research being conducted at the participating institutions and (ii) an opportunity for students to present and publish their work. Twenty-eight papers presented at the symposium are included in this proceedings. Some of the papers describe the progress of ongoing projects, and others contain the results of completed projects. Only brief summaries are given of the papers that will be published in full elsewhere. The program of the symposium and a list of the participants are included in the proceedings. ContentsCell Separations and Recycle Using an Inclined Settler, Ching-Yuan Lee, Robert H. Davis and Robert A. Sclafani Micromixing and Metabolism in Bioreactors: Characterization of a 14 L Fermenter, K.S. Wenger and E.H. Dunlop Production, Purification, and Hydrolysis Kinetics of Wild-Type and Mutant Glucoamylases from Aspergillus Awamori, Ufuk Bakir, Paul D. Oates, Hsiu-Mei Chen and Peter J. Reilly Dynamic Modeling of the Immune System, Barry Vant-Hull and Dhinakar S. Kompala Dynamic Modeling of Active Transport Across a Biological Cell: A Stochastic Approach, B.C. Shen, S.T. Chou, Y.Y. Chiu and L.T. Fan Electrokinetic Isolation of Bacterial Vesicles and Ribosomes, Debra T.L. Hawker, Robert H. Davis, Paul W. Todd, and Robert Lawson Application of Dynamic Programming for Fermentative Ethanol Production by Zymomonas mobilis, Sheyla L. Rivera and M. Nazmul Karim Biodegradation of PCP by Pseudomonas cepacia, R. Rayavarapu, S.K. Banerji, and R.K. Bajpai Modeling the Bioremediation of Contaminated Soil Aggregates: a Phenomenological Approach, S. Dhawan, L.E. Erickson and L.T. Fan Biospecific Adsorption of Glucoamylase-I from Aspergillus niger on Raw Starch, Bipin K. Dalmia and Zivko L. Nikolov Overexpression in Recombinant Mammalian Cells: Effect on Growth Rate and Genetic Instability, Jeffrey A. Kern and Dhinakar S. Kompala Structured Mathematical Modeling of Xylose Fermentation, A.K. Hilaly, M.N. Karim, I. C. Linden and S. Lastick A New Culture Medium for Carbon-limited Growth of Bacillus thuringiensis, W. -M. Liu and R.K. Bajpai Determination of Sugars and Sugar Alcohols by High Performance Ion Chromatography, T. J. Paskach, H.-P. Lieker, P.J. Reilly, and K. Thielecke Characterization of Poly-Asp Tailed B-Galactosidase, M.Q. Niederauer, C.E. Glatz, l.A. Suominen, C.F. Ford, and M.A. Rougvie Computation of Conformations and Energies of cr-Glucosyl Disaccharides, Jing Zepg, Michael K. Dowd, and Peter J. Reilly Pentachlorophenol Interactions with Soil, Shein-Ming Wei, Shankha K. Banerji, and Rakesh K. Bajpai Oxygen Transfer to Viscous Liquid Media in Three-Phase Fluidized Beds of Floating Bubble Freakers, Y. Kang, L.T. Fan, B.T. Min and S.D. Kim Studies on the Invitro Development of Chick Embryo, A. Venkatraman and T. Panda The Evolution of a Silicone Based Phase-Separated Gravity-Independent Bioreactor, Peter E. Villeneuve and Eric H. Dunlop Biodegradation of Diethyl Phthalate, Guorong Zhang, Kenneth F. Reardon and Vincent G. Murphy Microcosm Treatability of Soil Contaminated with Petroleum Hydrocarbons, P. Tuitemwong, S. Dhawan, B.M. Sly, L.E. Erickson and J.R. Schlup

Numerical modeling of marine radiocarbon reservoir ages during the last deglaciation

A critical problem in radiocarbon dating is the spatial and temporal variability of marine reservoir ages (MRAs). We assessed the MRA evolution during the last deglaciation by numerical modeling, applying a self-consistent iteration scheme in which an existing radiocarbon chronology (derived by Hughen et al., Quat. Sci. Rev., 25, pp. 3216-3227, 2006) was readjusted by transient, 3-D simulations of marine and atmospheric Delta14C. To estimate the uncertainties regarding the ocean ventilation during the last deglaciation, we considered various ocean overturning scenarios which are based on different climatic background states (PD: modern climate, GS: LGM climate conditions). Minimum and maximum MRAs are included in file 'MRAminmax_21-14kaBP.nc'. Three further files include MRAs according to equilibrium simulations of the preindustrial ocean (file 'C14age_preindustrial.nc'; this is an update of our results published in 2005) and of the glacial ocean (files 'C14age_spinupLGM_GS.nc' and 'C14age_spinupLGM_PD.nc').