First structural analysis of a naphthalene-based poly(ether ketone): Crystal and molecular simulation from X-ray powder data and diffraction modeling

Polycondensation of 2,6-dihydroxynaphthalene with 4,4'-bis(4"-fluorobenzoyl)biphenyl affords a novel, semicrystalline poly(ether ketone) with a melting point of 406 degreesC and glass transition temperature (onset) of 168 degreesC. Molecular modeling and diffraction-simulation studies of this polymer, coupled with data from the single-crystal structure of an oligomer model, have enabled the crystal and molecular structure of the polymer to be determined from X-ray powder data. This structure-the first for any naphthalene-containing poly(ether ketone)-is fully ordered, in monoclinic space group P2(1)/b, with two chains per unit cell. Rietveld refinement against the experimental powder data gave a final agreement factor (R-wp) of 6.7%.

Modeling the structure of amorphous MoS3: a neutron diffraction and reverse Monte Carlo study

A model for the structure of amorphous molybdenum trisulfide, a-MoS3, has been created using reverse Monte Carlo methods. This model, which consists of chains Of MoS6 units sharing three sulfurs with each of its two neighbors and forming alternate long, nonbonded, and short, bonded, Mo-Mo separations, is a good fit to the neutron diffraction data and is chemically and physically realistic. The paper identifies the limitations of previous models based on Mo-3 triangular clusters in accounting for the available experimental data.

Modeling energy consumption of dual-hop relay based MAC protocols in ad hoc networks

Given that the next and current generation networks will coexist for a considerable period of time, it is important to improve the performance of existing networks. One such improvement recently proposed is to enhance the throughput of ad hoc networks by using dual-hop relay-based transmission schemes. Since in ad hoc networks throughput is normally related to their energy consumption, it is important to examine the impact of using relay-based transmissions on energy consumption. In this paper, we present an analytical energy consumption model for dual-hop relay-based medium access control (MAC) protocols. Based on the recently reported relay-enabled Distributed Coordination Function (rDCF), we have shown the efficacy of the proposed analytical model. This is a generalized model and can be used to predict energy consumption in saturated relay-based ad hoc networks. This model can predict energy consumption in ideal environment and with transmission errors. It is shown that using a relay results in not only better throughput but also better energy efficiency. Copyright (C) 2009 Rizwan Ahmad et al.

Classification-based probabilistic modeling of texture transition for fast line search tracking and delineation

We introduce a classification-based approach to finding occluding texture boundaries. The classifier is composed of a set of weak learners, which operate on image intensity discriminative features that are defined on small patches and are fast to compute. A database that is designed to simulate digitized occluding contours of textured objects in natural images is used to train the weak learners. The trained classifier score is then used to obtain a probabilistic model for the presence of texture transitions, which can readily be used for line search texture boundary detection in the direction normal to an initial boundary estimate. This method is fast and therefore suitable for real-time and interactive applications. It works as a robust estimator, which requires a ribbon-like search region and can handle complex texture structures without requiring a large number of observations. We demonstrate results both in the context of interactive 2D delineation and of fast 3D tracking and compare its performance with other existing methods for line search boundary detection.

An agent based approach to distributed task modeling for co-operative task support

This paper describes the design and implementation of an agent based network for the support of collaborative switching tasks within the control room environment of the National Grid Company plc. This work includes aspects from several research disciplines, including operational analysis, human computer interaction, finite state modelling techniques, intelligent agents and computer supported co-operative work. Aspects of these procedures have been used in the analysis of collaborative tasks to produce distributed local models for all involved users. These models have been used as the basis for the production of local finite state automata. These automata have then been embedded within an agent network together with behavioural information extracted from the task and user analysis phase. The resulting support system is capable of task and communication management within the transmission despatch environment.

Modeling requirement driven architecture of adaptive healthcare system based on semiotics

In order to improve the quality of healthcare services, the integrated large-scale medical information system is needed to adapt to the changing medical environment. In this paper, we propose a requirement driven architecture of healthcare information system with hierarchical architecture. The system operates through the mapping mechanism between these layers and thus can organize functions dynamically adapting to user’s requirement. Furthermore, we introduce the organizational semiotics methods to capture and analyze user’s requirement through ontology chart and norms. Based on these results, the structure of user’s requirement pattern (URP) is established as the driven factor of our system. Our research makes a contribution to design architecture of healthcare system which can adapt to the changing medical environment.

Retrieval of sea surface temperature from space based on modeling of infrared radiative transfer: capabilities and limitations

The retrieval (estimation) of sea surface temperatures (SSTs) from space-based infrared observations is increasingly performed using retrieval coefficients derived from radiative transfer simulations of top-of-atmosphere brightness temperatures (BTs). Typically, an estimate of SST is formed from a weighted combination of BTs at a few wavelengths, plus an offset. This paper addresses two questions about the radiative transfer modeling approach to deriving these weighting and offset coefficients. How precisely specified do the coefficients need to be in order to obtain the required SST accuracy (e.g., scatter <0.3 K in week-average SST, bias <0.1 K)? And how precisely is it actually possible to specify them using current forward models? The conclusions are that weighting coefficients can be obtained with adequate precision, while the offset coefficient will often require an empirical adjustment of the order of a few tenths of a kelvin against validation data. Thus, a rational approach to defining retrieval coefficients is one of radiative transfer modeling followed by offset adjustment. The need for this approach is illustrated from experience in defining SST retrieval schemes for operational meteorological satellites. A strategy is described for obtaining the required offset adjustment, and the paper highlights some of the subtler aspects involved with reference to the example of SST retrievals from the imager on the geostationary satellite GOES-8.

Dynamic hydrological modeling in drylands with TRMM based rainfall

This paper introduces and evaluates DryMOD, a dynamic water balance model of the key hydrological process in drylands that is based on free, public-domain datasets. The rainfall model of DryMOD makes optimal use of spatially disaggregated Tropical Rainfall Measuring Mission (TRMM) datasets to simulate hourly rainfall intensities at a spatial resolution of 1-km. Regional-scale applications of the model in seasonal catchments in Tunisia and Senegal characterize runoff and soil moisture distribution and dynamics in response to varying rainfall data inputs and soil properties. The results highlight the need for hourly-based rainfall simulation and for correcting TRMM 3B42 rainfall intensities for the fractional cover of rainfall (FCR). Without FCR correction and disaggregation to 1 km, TRMM 3B42 based rainfall intensities are too low to generate surface runoff and to induce substantial changes to soil moisture storage. The outcomes from the sensitivity analysis show that topsoil porosity is the most important soil property for simulation of runoff and soil moisture. Thus, we demonstrate the benefit of hydrological investigations at a scale, for which reliable information on soil profile characteristics exists and which is sufficiently fine to account for the heterogeneities of these. Where such information is available, application of DryMOD can assist in the spatial and temporal planning of water harvesting according to runoff-generating areas and the runoff ratio, as well as in the optimization of agricultural activities based on realistic representation of soil moisture conditions.

CASCADE: An Agent Based Framework For Modeling The Dynamics Of Smart Electricity Systems

The Complex Adaptive Systems, Cognitive Agents and Distributed Energy (CASCADE) project is developing a framework based on Agent Based Modelling (ABM). The CASCADE Framework can be used both to gain policy and industry relevant insights into the smart grid concept itself and as a platform to design and test distributed ICT solutions for smart grid based business entities. ABM is used to capture the behaviors of diff erent social, economic and technical actors, which may be defi ned at various levels of abstraction. It is applied to understanding their interactions and can be adapted to include learning processes and emergent patterns. CASCADE models ‘prosumer’ agents (i.e., producers and/or consumers of energy) and ‘aggregator’ agents (e.g., traders of energy in both wholesale and retail markets) at various scales, from large generators and Energy Service Companies down to individual people and devices. The CASCADE Framework is formed of three main subdivisions that link models of electricity supply and demand, the electricity market and power fl ow. It can also model the variability of renewable energy generation caused by the weather, which is an important issue for grid balancing and the profi tability of energy suppliers. The development of CASCADE has already yielded some interesting early fi ndings, demonstrating that it is possible for a mediating agent (aggregator) to achieve stable demandfl attening across groups of domestic households fi tted with smart energy control and communication devices, where direct wholesale price signals had previously been found to produce characteristic complex system instability. In another example, it has demonstrated how large changes in supply mix can be caused even by small changes in demand profi le. Ongoing and planned refi nements to the Framework will support investigation of demand response at various scales, the integration of the power sector with transport and heat sectors, novel technology adoption and diffusion work, evolution of new smart grid business models, and complex power grid engineering and market interactions.

The use of computer-based learning tools for teaching and clinical purposes: Interactive computing strategy for Iraq

Medical universities and teaching hospitals in Iraq are facing a lack of professional staff due to the ongoing violence that forces them to flee the country. The professionals are now distributed outside the country which reduces the chances for the staff and students to be physically in one place to continue the teaching and limits the efficiency of the consultations in hospitals. A survey was done among students and professional staff in Iraq to find the problems in the learning and clinical systems and how Information and Communication Technology could improve it. The survey has shown that 86% of the participants use the Internet as a learning resource and 25% for clinical purposes while less than 11% of them uses it for collaboration between different institutions. A web-based collaborative tool is proposed to improve the teaching and clinical system. The tool helps the users to collaborate remotely to increase the quality of the learning system as well as it can be used for remote medical consultation in hospitals.

The impact of deformation strain on the formation of banded clouds in idealized modeling experiments

Experiments are performed using an idealized version of an operational forecast model to determine the impact on banded frontal clouds of the strength of deformational forcing, low-level baroclinicity, and model representation of convection. Line convection is initiated along the front, and slantwise bands extend from the top of the line-convection elements into the cold air. This banding is attributed primarily to M adjustment. The cross-frontal spreading of the cold pool generated by the line convection leads to further triggering of upright convection in the cold air that feeds into these slantwise bands. Secondary low-level bands form later in the simulations; these are attributed to the release of conditional symmetric instability. Enhanced deformation strain leads to earlier onset of convection and more coherent line convection. A stronger cold pool is generated, but its speed is reduced relative to that seen in experiments with weaker deformational strain, because of inhibition by the strain field. Enhanced low-level baroclinicity leads to the generation of more inertial instability by line convection (for a given capping height of convection), and consequently greater strength of the slantwise circulations formed by M adjustment. These conclusions are based on experiments without a convective-parametrization scheme. Experiments using the standard or a modified scheme for this model demonstrate known problems with the use of this scheme at the awkward 4 km grid length used in these simulations. Copyright © 2008 Royal Meteorological Society

Modeling the mechanisms that control in-stream dissolved organic carbon dynamics in upland and forested catchments

[1] We present a new, process-based model of soil and stream water dissolved organic carbon (DOC): the Integrated Catchments Model for Carbon (INCA-C). INCA-C is the first model of DOC cycling to explicitly include effects of different land cover types, hydrological flow paths, in-soil carbon biogeochemistry, and surface water processes on in-stream DOC concentrations. It can be calibrated using only routinely available monitoring data. INCA-C simulates daily DOC concentrations over a period of years to decades. Sources, sinks, and transformation of solid and dissolved organic carbon in peat and forest soils, wetlands, and streams as well as organic carbon mineralization in stream waters are modeled. INCA-C is designed to be applied to natural and seminatural forested and peat-dominated catchments in boreal and temperate regions. Simulations at two forested catchments showed that seasonal and interannual patterns of DOC concentration could be modeled using climate-related parameters alone. A sensitivity analysis showed that model predictions were dependent on the mass of organic carbon in the soil and that in-soil process rates were dependent on soil moisture status. Sensitive rate coefficients in the model included those for organic carbon sorption and desorption and DOC mineralization in the soil. The model was also sensitive to the amount of litter fall. Our results show the importance of climate variability in controlling surface water DOC concentrations and suggest the need for further research on the mechanisms controlling production and consumption of DOC in soils.

Hydraulic modeling of runoff over a rough surface under partial inundation

This study presents a numerical method to derive the Darcy- Weisbach friction coefficient for overland flow under partial inundation of surface roughness. To better account for the variable influence of roughness with varying levels of emergence, we model the flow over a network which evolves as the free surface rises. This network is constructed using a height numerical map, based on surface roughness data, and a discrete geometry skeletonization algorithm. By applying a hydraulic model to the flows through this network, local heads, velocities, and Froude and Reynolds numbers over the surface can be estimated. These quantities enable us to analyze the flow and ultimately to derive a bulk friction factor for flow over the entire surface which takes into account local variations in flow quantities. Results demonstrate that although the flow is laminar, head losses are chiefly inertial because of local flow disturbances. The results also emphasize that for conditions of partial inundation, flow resistance varies nonmonotonically but does generally increase with progressive roughness inundation.

Case study of the use of remotely sensed data for modeling flood inundation on the river Severn, UK.

A methodology for using remotely sensed data to both generate and evaluate a hydraulic model of floodplain inundation is presented for a rural case study in the United Kingdom: Upton-upon-Severn. Remotely sensed data have been processed and assembled to provide an excellent test data set for both model construction and validation. In order to assess the usefulness of the data and the issues encountered in their use, two models for floodplain inundation were constructed: one based on an industry standard one-dimensional approach and the other based on a simple two-dimensional approach. The results and their implications for the future use of remotely sensed data for predicting flood inundation are discussed. Key conclusions for the use of remotely sensed data are that care must be taken to integrate different data sources for both model construction and validation and that improvements in ground height data shift the focus in terms of model uncertainties to other sources such as boundary conditions. The differences between the two models are found to be of minor significance.

Cone model-based SEP event calculations for applications to multipoint observations

The problem of modeling solar energetic particle (SEP) events is important to both space weather research and forecasting, and yet it has seen relatively little progress. Most important SEP events are associated with coronal mass ejections (CMEs) that drive coronal and interplanetary shocks. These shocks can continuously produce accelerated particles from the ambient medium to well beyond 1 AU. This paper describes an effort to model real SEP events using a Center for Integrated Space weather Modeling (CISM) MHD solar wind simulation including a cone model of CMEs to initiate the related shocks. In addition to providing observation-inspired shock geometry and characteristics, this MHD simulation describes the time-dependent observer field line connections to the shock source. As a first approximation, we assume a shock jump-parameterized source strength and spectrum, and that scatter-free transport occurs outside of the shock source, thus emphasizing the role the shock evolution plays in determining the modeled SEP event profile. Three halo CME events on May 12, 1997, November 4, 1997 and December 13, 2006 are used to test the modeling approach. While challenges arise in the identification and characterization of the shocks in the MHD model results, this approach illustrates the importance to SEP event modeling of globally simulating the underlying heliospheric event. The results also suggest the potential utility of such a model for forcasting and for interpretation of separated multipoint measurements such as those expected from the STEREO mission.