Depth profiles of dissolved sulfide and sulfate in the pore water of hydrocarbon seep sediments offshore Pakistan

The interaction between fluid seepage, bottom water redox, and chemosynthetic communities was studied at cold seeps across one of the world's largest oxygen minimum zones (OMZ) located at the Makran convergent continental margin. Push cores were obtained from seeps within and below the core-OMZ with a remotely operated vehicle. Extracted sediment pore water was analyzed for sulfide and sulfate concentrations. Depending on oxygen availability in the bottom water, seeps were either colonized by microbial mats or by mats and macrofauna. The latter, including ampharetid polychaetes and vesicomyid clams, occurred in distinct benthic habitats, which were arranged in a concentric fashion around gas orifices. At most sites colonized by microbial mats, hydrogen sulfide was exported into the bottom water. Where macrofauna was widely abundant, hydrogen sulfide was retained within the sediment. Numerical modeling of pore water profiles was performed in order to assess rates of fluid advection and bioirrigation. While the magnitude of upward fluid flow decreased from 11 cm yr**-1 to <1 cm yr**-1 and the sulfate/methane transition (SMT) deepened with increasing distance from the central gas orifice, the fluxes of sulfate into the SMT did not significantly differ (6.6-9.3 mol m**-2 yr**-1). Depth-integrated rates of bioirrigation increased from 120 cm yr**-1 in the central habitat, characterized by microbial mats and sparse macrofauna, to 297 cm yr**-1 in the habitat of large and few small vesicomyid clams. These results reveal that chemosynthetic macrofauna inhabiting the outer seep habitats below the core-OMZ efficiently bioirrigate and thus transport sulfate down into the upper 10 to 15 cm of the sediment. In this way the animals deal with the lower upward flux of methane in outer habitats by stimulating rates of anaerobic oxidation of methane (AOM) with sulfate high enough to provide hydrogen sulfide for chemosynthesis. Through bioirrigation, macrofauna engineer their geochemical environment and fuel upward sulfide flux via AOM. Furthermore, due to the introduction of oxygenated bottom water into the sediment via bioirrigation, the depth of the sulfide sink gradually deepens towards outer habitats. We therefore suggest that - in addition to the oxygen levels in the water column, which determine whether macrofaunal communities can develop or not - it is the depth of the SMT and thus of sulfide production that determines which chemosynthetic communities are able to exploit the sulfide at depth. We hypothesize that large vesicomyid clams, by efficiently expanding the sulfate zone down into the sediment, could cut off smaller or less mobile organisms, as e.g. small clams and sulfur bacteria, from the sulfide source.

Time-series Luminance Distribution Maps: implementation of annual daylight simulation methods for occupant visual comfort analysis

Thesis (Master's)--University of Washington, 2016-06

The Microphysical Structure of Mesoscale Convective Systems

Thesis (Ph.D.)--University of Washington, 2016-05

Influence apart from Adoption: How Interaction between Programming and Scientific Practices Shapes Modes of Inquiry in Four Oceanography Teams

Thesis (Ph.D.)--University of Washington, 2016-06

Remotely sensed data for ecosystem analyses: Combining hierarchy and scene models

Remotely sensed data have been used extensively for environmental monitoring and modeling at a number of spatial scales; however, a limited range of satellite imaging systems often. constrained the scales of these analyses. A wider variety of data sets is now available, allowing image data to be selected to match the scale of environmental structure(s) or process(es) being examined. A framework is presented for use by environmental scientists and managers, enabling their spatial data collection needs to be linked to a suitable form of remotely sensed data. A six-step approach is used, combining image spatial analysis and scaling tools, within the context of hierarchy theory. The main steps involved are: (1) identification of information requirements for the monitoring or management problem; (2) development of ideal image dimensions (scene model), (3) exploratory analysis of existing remotely sensed data using scaling techniques, (4) selection and evaluation of suitable remotely sensed data based on the scene model, (5) selection of suitable spatial analytic techniques to meet information requirements, and (6) cost-benefit analysis. Results from a case study show that the framework provided an objective mechanism to identify relevant aspects of the monitoring problem and environmental characteristics for selecting remotely sensed data and analysis techniques.

Refined method of potential enhancement in the equilibria characterization of activated carbon. Comparison with GCMC and DFT

In this paper, we present a technique for equilibria characterization of activated carbon having slit-shaped pores. This method was first developed by Do (Do, D. D. A new method for the characterisation of micro-mesoporous materials. Presented at the International Symposium on New Trends in Colloid and Interface Science, September 24-26, 1998 Chiba, Japan) and applied by his group and other groups for characterization of pore size distribution (PSD) as well as adsorption equilibria determination of a wide range of hydrocarbons. It is refined in this paper and compared with the grand canonical Monte Carlo (GCMG) simulation and density functional theory (DFT). The refined theory results in a good agreement between the pore filling pressure versus pore width and those obtained by GCMG and DFT. Furthermore, our local isotherms are qualitatively in good agreement with those obtained by the GCMC simulations. The main advantage of this method is that it is about 4 orders of magnitude faster than the GCMC simulations, making it suitable for optimization studies and design purposes. Finally, we apply our method and the GCMG in the derivation of the PSD of a commercial activated carbon. It was found that the PSD derived from our method is comparable to that derived from the GCMG simulations.

Gene duplication and hierarchical modularity in intracellular interaction networks

Networks of interactions evolve in many different domains. They tend to have topological characteristics in common, possibly due to common factors in the way the networks grow and develop. It has been recently suggested that one such common characteristic is the presence of a hierarchically modular organization. In this paper, we describe a new algorithm for the detection and quantification of hierarchical modularity, and demonstrate that the yeast protein-protein interaction network does have a hierarchically modular organization. We further show that such organization is evident in artificial networks produced by computational evolution using a gene duplication operator, but not in those developing via preferential attachment of new nodes to highly connected existing nodes. (C) 2004 Elsevier Ireland Ltd. All rights reserved.

Using the canonical modelling approach to simplify the simulation of function in functional-structural plant models

Functional-structural plant models that include detailed mechanistic representation of underlying physiological processes can be expensive to construct and the resulting models can also be extremely complicated. On the other hand, purely empirical models are not able to simulate plant adaptability and response to different conditions. In this paper, we present an intermediate approach to modelling plant function that can simulate plant response without requiring detailed knowledge of underlying physiology. Plant function is modelled using a 'canonical' modelling approach, which uses compartment models with flux functions of a standard mathematical form, while plant structure is modelled using L-systems. Two modelling examples are used to demonstrate that canonical modelling can be used in conjunction with L-systems to create functional-structural plant models where function is represented either in an accurate and descriptive way, or in a more mechanistic and explanatory way. We conclude that canonical modelling provides a useful, flexible and relatively simple approach to modelling plant function at an intermediate level of abstraction.

GCMC-surface area of carbonaceous materials with N-2 and Ar adsorption as an alternative to the classical BET method

In this paper we apply a new method for the determination of surface area of carbonaceous materials, using the local surface excess isotherms obtained from the Grand Canonical Monte Carlo simulation and a concept of area distribution in terms of energy well-depth of solid–fluid interaction. The range of this well-depth considered in our GCMC simulation is from 10 to 100 K, which is wide enough to cover all carbon surfaces that we dealt with (for comparison, the well-depth for perfect graphite surface is about 58 K). Having the set of local surface excess isotherms and the differential area distribution, the overall adsorption isotherm can be obtained in an integral form. Thus, given the experimental data of nitrogen or argon adsorption on a carbon material, the differential area distribution can be obtained from the inversion process, using the regularization method. The total surface area is then obtained as the area of this distribution. We test this approach with a number of data in the literature, and compare our GCMC-surface area with that obtained from the classical BET method. In general, we find that the difference between these two surface areas is about 10%, indicating the need to reliably determine the surface area with a very consistent method. We, therefore, suggest the approach of this paper as an alternative to the BET method because of the long-recognized unrealistic assumptions used in the BET theory. Beside the surface area obtained by this method, it also provides information about the differential area distribution versus the well-depth. This information could be used as a microscopic finger-print of the carbon surface. It is expected that samples prepared from different precursors and different activation conditions will have distinct finger-prints. We illustrate this with Cabot BP120, 280 and 460 samples, and the differential area distributions obtained from the adsorption of argon at 77 K and nitrogen also at 77 K have exactly the same patterns, suggesting the characteristics of this carbon.

Rice morphogenesis and plant architecture: Measurement, specification and the reconstruction of structural development by 3D architectural modelling

Background and Aims The morphogenesis and architecture of a rice plant, Oryza sativa, are critical factors in the yield equation, but they are not well studied because of the lack of appropriate tools for 3D measurement. The architecture of rice plants is characterized by a large number of tillers and leaves. The aims of this study were to specify rice plant architecture and to find appropriate functions to represent the 3D growth across all growth stages. Methods A japonica type rice, 'Namaga', was grown in pots under outdoor conditions. A 3D digitizer was used to measure the rice plant structure at intervals from the young seedling stage to maturity. The L-system formalism was applied to create '3D virtual rice' plants, incorporating models of phenological development and leaf emergence period as a function of temperature and photoperiod, which were used to determine the timing of tiller emergence. Key Results The relationships between the nodal positions and leaf lengths, leaf angles and tiller angles were analysed and used to determine growth functions for the models. The '3D virtual rice' reproduces the structural development of isolated plants and provides a good estimation of the fillering process, and of the accumulation of leaves. Conclusions The results indicated that the '3D virtual rice' has a possibility to demonstrate the differences in the structure and development between cultivars and under different environmental conditions. Future work, necessary to reflect both cultivar and environmental effects on the model performance, and to link with physiological models, is proposed in the discussion.

Functional-structural plant modelling using a combination of architectural analysis, L-systems and a canonical model of function

This paper presents a new method for producing a functional-structural plant model that simulates response to different growth conditions, yet does not require detailed knowledge of underlying physiology. The example used to present this method is the modelling of the mountain birch tree. This new functional-structural modelling approach is based on linking an L-system representation of the dynamic structure of the plant with a canonical mathematical model of plant function. Growth indicated by the canonical model is allocated to the structural model according to probabilistic growth rules, such as rules for the placement and length of new shoots, which were derived from an analysis of architectural data. The main advantage of the approach is that it is relatively simple compared to the prevalent process-based functional-structural plant models and does not require a detailed understanding of underlying physiological processes, yet it is able to capture important aspects of plant function and adaptability, unlike simple empirical models. This approach, combining canonical modelling, architectural analysis and L-systems, thus fills the important role of providing an intermediate level of abstraction between the two extremes of deeply mechanistic process-based modelling and purely empirical modelling. We also investigated the relative importance of various aspects of this integrated modelling approach by analysing the sensitivity of the standard birch model to a number of variations in its parameters, functions and algorithms. The results show that using light as the sole factor determining the structural location of new growth gives satisfactory results. Including the influence of additional regulating factors made little difference to global characteristics of the emergent architecture. Changing the form of the probability functions and using alternative methods for choosing the sites of new growth also had little effect. (c) 2004 Elsevier B.V. All rights reserved.

Adsorption of flexible n-alkane on graphitized thermal carbon black: analysis of adsorption isotherm by means of GCMC simulation

In this paper, we investigate the suitability of the grand canonical Monte Carlo in the description of adsorption equilibria of flexible n-alkane (butane, pentane and hexane) on graphitized thermal carbon black. Potential model of n-alkane of Martin and Siepmann (J. Phys. Chem. 102 (1998) 2569) is employed in the simulation, and we consider the flexibility of molecule in the simulation. By this we study two models, one is the fully flexible molecular model in which n-alkane is subject to bending and torsion, while the other is the rigid molecular model in which all carbon atoms reside on the same plane. It is found that (i) the adsorption isotherm results of these two models are close to each other, suggesting that n-alkane model behaves mostly as rigid molecules with respect to adsorption although the isotherm for longer chain n-hexane is better described by the flexible molecular model (ii) the isotherms agree very well with the experimental data at least up to two layers on the surface.

Is health care seeking for irritable bowel syndrome and functional dyspepsia a socially learned response to illness?

In a population-based study of 207 subjects with irritable bowel syndrome (IBS) or functional dyspepsia (FD) and controls (n = 100), we aimed to determine whether dimensions of abnormal illness behavior from the Abnormal Illness Behaviour Questionnaire and aspects of social learning of illness behavior from the Social Learning of Illness Behaviour scale were independent predictors of health care seeking for IBS and FD. Results showed that dimensions of abnormal illness behavior and aspects of social learning of illness behavior (encouragement, reinforcement, and modeling) did not significantly differentiate between consulters and nonconsulters with IBS and/or FD. The Disease Conviction scale (OR = 1.55; 95% CI, 1.15-2.09) of the Abnormal Illness Behaviour Questionnaire was an independent predictor of having a diagnosis of IBS and/or FD, independent of age and gender, psychiatric diagnoses, and symptom severity. We conclude that a belief in the presence of serious pathology characterizes community subjects with IBS and FD, but not health care seeking.

Comparison of beam theory and finite-element analysis with in vivo bone strain data from the alligator cranium

The mechanical behavior of the vertebrate skull is often modeled using free-body analysis of simple geometric structures and, more recently, finite-element (FE) analysis. In this study, we compare experimentally collected in vivo bone strain orientations and magnitudes from the cranium of the American alligator with those extrapolated from a beam model and extracted from an FE model. The strain magnitudes predicted from beam and FE skull models bear little similarity to relative and absolute strain magnitudes recorded during in vivo biting experiments. However, quantitative differences between principal strain orientations extracted from the FE skull model and recorded during the in vivo experiments were smaller, and both generally matched expectations from the beam model. The differences in strain magnitude between the data sets may be attributable to the level of resolution of the models, the material properties used in the FE model, and the loading conditions (i.e., external forces and constraints). This study indicates that FE models and modeling of skulls as simple engineering structures may give a preliminary idea of how these structures are loaded, but whenever possible, modeling results should be verified with either in vitro or preferably in vivo testing, especially if precise knowledge of strain magnitudes is desired. (c) 2005 Wiley-Liss, Inc.