Simplified numerical model for clarifying scaling behavior in the intermediate dispersion regime in homogeneous porous media The dispersion of solute in porous media shows a non-linear increase in the transition from diffusion to advection dominated dispersion as the flow velocity is raised. In the past, the behavior in this intermediate regime has been explained with a variety of models. We present and use a simplified numerical model which does not contain any turbulence, Taylor dispersion, or fractality. With it, we show that the non-linearity in the intermediate regime nevertheless occurs. Furthermore, we show that that the intermediate regime can be regarded as a phase transition between random, diffusive transport at low flow velocity and ordered transport controlled by the geometry of the pore space at high flow velocities. This phase transition explains the firstorder behavior in the intermediate regime. A new quantifier, the ratio of the amount of solute in dominantly advective versus dominantly diffusive pore channels, plays the role of 'order parameter' of this phase transition. Taylor dispersion, often invoked to explain the supra-linear behavior of longitudinal dispersion in this regime, was found not to be of primary importance. The novel treatment of the intermediate regime paves the way for a more accurate description of dispersion as a function of flow velocity, spanning the whole range of Péclet numbers relevant to practical applications, such as ground water remediation. Transport of dissolved solutes in pore fluids in homogeneous porous media results from the synergy between advection and diffusion [1, 2] . Despite its importance in many applications and fields of research (e.g., groundwater remediation), this process is not yet understood in full detail. Flow through a porous medium causes an increased effective diffusion of the solute, termed dispersion, due to variations in flow velocity within and between the individual pore channels and due to the tortuous pathways the fluid follows through the pores. The corresponding dispersion coefficients are commonly applied in models based on the advection-diffusion equation (ADE) to describe spreading of solute in porous media, for example pollutant plumes in ground water, although one should be aware that the ADE is only valid under rather restrictive conditions [3] . Although it is generally agreed that dispersion increases with flow velocity, there is no agreement on the exact relationship between the dispersion coefficient and controlling parameters, such as flow velocity, pore geometry, fluid viscosity, etc. [4] .. To study solute transport in homogeneous porous media, a sample of fluid-filled porous material is subjected to an external pressure head in a specific direction (taken to be the x-direction). This results in a fluid flow velocity v 0 through the medium, usually expressed in terms of the Péclet number, Pe = v 0 G/D, where G is a typical microscopic length scale (grain size), and D a ('molecular') diffusion coefficient (of the solute in the fluid). Then, the dispersion of an initially concentrated distribution of solute is studied as it is advected through the medium, while simultaneously experiencing diffusion.. The observed longitudinal (D x ) and transverse (D y ) dispersion as a function of Péclet number (flow velocity) is often described by a disjunct set of up to five dispersional regimes [5, 2, 6, 7] , using a separate functional relationship (sometimes referred to as 'correlation') between Péclet number and dispersion, D x,y (Pe), in each regime. Typically, the following regimes are discerned, although the boundaries between the regimes vary somewhat between authors: (i) The molecular diffusion regime (Pe < 0.1 − 0.3); (ii) the transition regime (0.1 − 0.3 < Pe < 5); (iii) the major regime (also known as the power law regime [8] ) (5 < Pe < 250 − 4000); (iv) the mechanical dispersion regime (250 − 4000 < Pe); (v) the high Pe number regime, sometimes called the inertial or turbulent regime. Here, we are concerned with laminar flow only. We will jointly refer to regimes (ii) and (iii) as the 'intermediate regime', i.e., intermediate between the diffusive and mechanical dispersion regimes.. Quite often, the dispersion in each regime is described by a power law, i.e., D x,y (Pe) ∝ Pe αx,y . Not surprisingly, for regime (i), α x,y = 0, while for regime (iv), α x,y = 1. However, in the intermediate regime, exponents differing from these limiting values have been reported to fit experimental data, which has given rise to speculation about their origin [9, 7] . Reported values for α x are 1.2 − 1.3 ( [9] and references therein; [7] ), while those for α y are typically around 0.5 − 0.7 [10, 11, 12] .. Recently, a simplified heuristic model was proposed to replace this disjunct description of dispersion by a single, unified expression [13, 14] . The model assumes that the advective and diffusive transport mechanisms compete in the pore channels. Then, as the mean flow velocity (or pressure head) is increased, transport in ever more pore channels along the solute flow path through the medium will be advection-dominated. By making a simple assumption regarding the growth of the ratio between advection and diffusion dominated channels as the flow is increased, an expression for the net dispersion was derived. The expression successfully describes experimental data for dispersion in homogeneous porous media over the full range of Péclet numbers in laminar flow (regimes (i) to (iv)). In particular, it reproduces the faster than linear growth of the longitudinal dispersion with Péclet number in the intermediate regime, corresponding to an apparent exponent α x > 1. It was claimed that this behavior could be understood from the statistical behavior of tracers in the pore channels.. To clarify the origin of this purported statistical behavior, presumed quite generic for porous media, here we study a highly simplified model for porous media consisting of a network of (pore) channels [15, 16] . In order to obtain a clear vision of the impact of the statistical behavior mentioned above on dispersion, the model we chose for this study is as minimalistic as possible, removing any physical mechanisms, such as turbulence and Taylor dispersion (see Section 2 below), that might affect these statistical properties. Thus, along the network connections, transport is one-dimensional and strictly diffusive and/or advective. The effective longitudinal and transverse dispersion coefficients are extracted from the final numerical solution, after evolving the system in time. It will be shown that this model does indeed reproduce the dispersion regimes and produces exponents α x,y very similar to those obtained in experiments on actual porous media. In this way, the minimum ingredients giving rise to the observed dispersional behavior are identified. Furthermore, we will extract statistical information regarding the microscopic transport process that will elucidate the origin of the observed behavior.. Clearly, the model has only limited relevance as de detailed model of real systems. However, we emphasize that this is not its purpose. Rather, the model is constructed to discriminate sharply between qualitatively and quantitatively different physical mechanisms. Discrimination is achieved by the combination of several assumptions, namely: (a) Highly complex threedimensional porous materials are modeled by a simple two-dimensional network of infinitely thin connections linking nodes. (b) Fluid flow through the system is imposed and not influenced by the presence of the solute; in other words, the solute fraction is assumed to be infinitesimally small. (c) The fluid flow itself is incompressible, which is a reasonable assumption even in a realistic porous system when the fluid chosen is water or similar. (d) The solute is passively transported by the fluid and is not assumed to be subject to independent transport equations (i.e., the solute has no inertia and it is not reactive).. This simplified model is used to study the effect of network topology on dispersion. The philosophy of our approach is similar to that of [9, 8] . Here, however, we render the model minimalistically. The objective is to expose the essential ingredients for description of solute transport in porous media. An important aspect of the model is the use of continuum transport equations for the solute. This effectively is the use of an infinite number of tracers, which leads to high accuracy results (not easy to obtain using tracers [17] ). Another important aspect is that the numerical model is specifically designed to handle the wide spread of flow velocities in individual channels, typical of general porous media. In this work, we have modeled transport through porous media by means of a two-dimensional network of one-dimensional channels ('pores') linking nodes. Along each channel, advection and diffusion was modeled using the one-dimensional advection-diffusion equation. The numerical solution method is based on the requirement that no solute is lost between network nodes. This fact stabilizes the numerical time evolution of the solution, even at very high advective velocities. The latter constitutes an advantage for the study of dispersion in a network with a wide range of local flow velocities.. We studied a range of network types, advancing the time solution from an initial state in which the solute was concentrated at a central node to a time when a stop criterion was satisfied. At the stop time, the effective longitudinal and transverse dispersion coefficients were determined. For each network, a range of flow velocities was explored.. The results indicate that the main effects of dispersion in porous media observed in laboratory experiments in homogenous porous media (in particular, the behavior of the dispersion coefficients in the intermediate regime, as already predicted in [13] ) can be reproduced using a minimal model containing only the mentioned ingredients: a simplified pore geometry (network), diffusion, and advection. Thus, some hypothetic dispersion mechanisms invoked by other authors (e.g., Taylor dispersion, anomalous diffusion or fractality [29, 30, 31, 32] ) are not needed to obtain these effects, as the observed dispersional behavior already emerges spontaneously in this highly simplified model.. The results also constitute a verification of the basic assumption underlying the analytic model of [13] , namely the growth of n v /n 0 as v 0 is increased, although the actual functional form depends on the specific network type. This novel quantity therefore plays a crucial role in the understanding of the origin of the nonlinear behavior of the dispersion coefficients in the intermediate regime.. An analysis of the distribution of solute over channels with specific Pe loc values indicates that this distribution experiences a 'phase transition' from an unordered low-velocity state to an ordered high-velocity state. The width and skewness of the distribution peak in the intermediate regime, at the velocity (v 0 ≃ 10) where the growth exponent of longitudinal dispersion (α x ) exceeds 1. Transport in the highly simplified model for porous media studied here (a network of nodes connected by one-dimensional channels, while transport through the channels is purely advective and diffusive) exhibits several of the features also observed in laboratory experiments on porous media: (a) the diffusive regime at low Péclet number and (b) the mechanical dispersion regime at high Péclet number are correctly recovered. In the intermediate regime, (c) the longitudinal dispersion generally grows faster than linear (α x > 1), whereas (d) the transverse dispersion grows much slower (and α y < 1). An exception to this, among the various networks studied, is the tile grid, in which longitudinal connectivity was purposely reduced by a factor of two with respect to the square grid. This reduced longitudinal connectivity brings longitudinal dispersion down to a level comparable to the transverse dispersion, showing that network topology affects dispersion in a profound manner. Fig. 2 is illustrative of the generic behavior of dispersion as the flow velocity v 0 is increased at constant diffusivity D: the solute tends to be drawn preferentially into advection-dominated channels as the fluid velocity increases. In other words, at low velocity, the solute expands randomly through all types of channel, but at high velocity, it explores much more advection-dominated (i.e., horizontal) channels than diffusion-dominated (vertical) channels. Hence, on average, the solute will tend to spend more time in advection-dominated channels as v 0 is raised. Note that this is the basic assumption underlying the heuristic model of [13] .. The fact that this model qualitatively reproduces the dispersional behavior observed in actual experiments on homogeneous porous media, while Taylor dispersion is absent by definition, implies that Taylor dispersion is not required to obtain α x > 1 in the intermediate regime. While this does not prove that Taylor dispersion is not relevant in actual porous media, it suggests that the relevance of Taylor dispersion for the explanation of the observed behavior (α x > 1) needs to be reviewed carefully.. Perfectly regular grids such as the square and hexagonal grids presented above are somewhat pathological and suffer from the fact that many channels are exactly perpendicular to the mean flow direction (the x-axis). This means that these channels are 'stagnant', and transport through them is purely diffusive, regardless of v 0 . As v 0 is increased, the transport flux through these channels becomes negligible with respect to the total flux, so that the transport topology of the system becomes effectively one-dimensional. To avoid this topological breakdown, the positions of the main nodes of the network are 'wiggled' slightly from their nominal positions. With the square and hexagonal grids, the quantifier n v /n 0 stagnates in the range 10 < Pe < 100 (cf. Figs. 3 and 9) . It turns out that in this range, there is a gradual shift of the solute concentration towards channels with higher velocities, which however is undetected by the n v /n 0 quantifier since the the corresponding part of the solute already resides in channels with Pe loc > 1 (as can be verified by computing a graph like Fig. 13 for these cases) . This effect arises because of the regular structure of the grid, causing the channels to fall into a very reduced number of classes.. This situation is considered somewhat unrealistic, as actual porous media will never be perfectly regular (not to mention the fact that there, structure is three-dimensional rather than two-dimensional). By comparison with the regular grids, the "Elle" grid has the advantage of offering more gradual (realistic?) variations of quantities such as n v /n 0 , facilitating their study and understanding. Thus, we focus attention on the "Elle" grid results.. The statistical quantifier n v /n 0 , indicating the 'number of tracers' (amount of solute) in advective channels versus diffusive channels, increases systematically as v 0 is raised. The point where n v /n 0 reaches 1 was found to immediately precede the moment when α x reaches 1 for all grids (with the exception of the tile grid, in which α x ≤ 1). This observation is consistent with the analytic model of [13] , in which the growth of the quantifier n v /n 0 with v 0 was hypothesized to be the cause of α x > 1 in the intermediate Péclet number regime in porous media: as v 0 increases, not only does the velocity of the solute tracers increase (trivially), but also the number of tracers in advective (n v ) versus diffusive (n 0 ) channels, thus giving rise to a faster than linear increase of global longitudinal dispersion in the intermediate regime.. Furthermore, with the "Elle" (two-dimensional foam) network, Fig. 12 shows that n v /n 0 grows linearly, n v /n 0 ∝ v γ 0 , γ ≃ 1.0, in the range 6 < v 0 < 200. For smaller values of v 0 , fluid flow is so slow that no channels are classified as 'advective' (n v ≃ 0), while for higher values of v 0 , no channels are classified as 'diffusive' (n 0 ≃ 0). Thus, the fact that this power law only appears to exist over a finite range of v 0 values is merely due to the crudeness of the channel classification criterion. The main message of this result is that the ratio of solute in 'advective' and 'diffusive' channels increases systematically as the fluid flow v 0 is increased, in accordance with the prediction of [13] .. When plotting the distribution of solute over channels with different Pe loc values as a function of the fluid velocity v 0 (Fig. 13) , it appears that the system experiences a 'phase transition' from low fluid velocities (v 0 1) to high velocities (v 0 10). This phase transition is reflected in the width and skewness of the (logarithmic) distribution of Pe loc , Fig. 14 , which peak at the transition. The phase transition arises spontaneously from the complexity of the flow patterns in the two-dimensional network, and is related to the super-linear growth of the dispersion D x (Pe), i.e., α x > 1.. The idea of a phase transition is justified from the point of view that at very low velocities, mean solute motion is essentially independent from the imposed advection, whereas at high velocities it moves almost exclusively with the (deterministic, externally imposed) fluid flow, corresponding to a change from an uncorrelated to a correlated state. This change of state is not gradual, but involves a rather sharp correlation peak, as shown in Fig. 15 , which can be understood from the explanation given in the previous section. Here, we simply note that a sharp increase of correlation is typical of phase transitions [25] .. Note that the quantifier n v /n 0 plays the role of an 'order parameter' of the phase transition. In particular, its derivative with respect to Pe (or 'susceptibility') is large at around v 0 = 1−5 (Fig. 12) , which roughly corresponds to the point where the width of the distribution of Pe loc , Fig. 14 , becomes large.. We emphasize that this model only offers a limited degree of realism due to its simplicity. However, the statistical analysis outlined here should be easy to apply to more realistic simulations of tracer transport in porous media [26, 27] and to detailed tracer velocity measurements in actual porous material samples facilitated by NMR techniques [28] . That would provide final and definitive support for the clarification of the origin of the enhanced dispersion exponent, α x > 1, in the intermediate regime, as discussed here. Also, the analysis of the motion of individual tracers should allow a more complete analysis of the phase transition indicated here: tracer motion makes a transition from random motion (in the diffusive phase) to deterministic motion (in the advective phase). This change should be reflected in the correlation length between the velocities of individual tracers. In the following, we will set D ij = D = 1, physically corresponding to a homogenous fluid at a constant temperature. The diameter of the network cells is typically G = 1, although the definition of 'cell diameter' is not unambiguous for all types of network. With these choices, the Péclet number Pe = G · v 0 /D is equal to v 0 itself, which is useful for the interpretation of the results below in relation to experimental data. A priori, these numbers have not yet been assigned a specific physical dimension. However, if we use mm as the spatial unit, and s as the time unit, then G is in mm and D in mm 2 /s, which actually makes these choices very close to the physical values used in many sand box or bead experiments.. Edge boundary conditions are the default ones (Neumann), although this is of little consequence as time integration is stopped when the distribution p reaches the boundary. We define a stopping criterion based on the ratio. Initially, R = 0 as the initial condition is p i = 0 for all i except at one centrally located node. As p evolves in time, the distribution broadens and after some time the value of p at the edge nodes begins to increase, such that R increases. We stop the time integration when R > θ, where θ is a threshold. Here, we set θ = 0.001. The network size should be sufficiently large to allow any initial transient to decay. Typically, network sizes of about 100 cells in each dimension should be more than sufficient, although this will depend somewhat on the specific grid topology.. Before discussing the numerical results, we reiterate that this model does not contain Taylor dispersion. First, as transport through every network channel is one-dimensional, there are no neighboring flow lines with velocity differences that can be smoothed out by diffusion (see Section 2.3). Second, a hypothetical tracer particle crossing from one flow line to another at a network intersection node only experiences the local flow velocity at every time instant, so there is no mixing of flow velocities as would occur with the Taylor dispersion mechanism. Third, along each network channel, the diffusion D is constant, so there is also no 'effective' Taylor dispersion (which one might introduce by defining D ∝ v 2 ).

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Annotation-based feature extraction from sets of SBML models Background: Model repositories such as BioModels Database provide computational models of biological systems for the scientific community. These models contain rich semantic annotations that link model entities to concepts in well-established bio-ontologies such as Gene Ontology. Consequently, thematically similar models are likely to share similar annotations. Based on this assumption, we argue that semantic annotations are a suitable tool to characterize sets of models. These characteristics improve model classification, allow to identify additional features for model retrieval tasks, and enable the comparison of sets of models.In this paper we discuss four methods for annotation-based feature extraction from model sets. We tested all methods on sets of models in SBML format which were composed from BioModels Database. To characterize each of these sets, we analyzed and extracted concepts from three frequently used ontologies, namely Gene Ontology, ChEBI and SBO. We find that three out of the methods are suitable to determine characteristic features for arbitrary sets of models: The selected features vary depending on the underlying model set, and they are also specific to the chosen model set. We show that the identified features map on concepts that are higher up in the hierarchy of the ontologies than the concepts used for model annotations. Our analysis also reveals that the information content of concepts in ontologies and their usage for model annotation do not correlate.Annotation-based feature extraction enables the comparison of model sets, as opposed to existing methods for model-to-keyword comparison, or model-to-model comparison. Thanks to standardization efforts in Systems Biology [1] , modelers today have access to high-quality, curated models in standard formats. The Systems Biology Markup Language (SBML) [2] is an XML-based standard format to encode models as interactions between biological entities. The emerging networks are furthermore enriched with semantic annotations [3] which link model parts to external knowledge in domain-specific ontologies (bioontologies) [4] . Many SBML models live in open model repositories such as BioModels Database [5] , the Physiome Model Repository [6] , or JWS Online [7] . These repositories distribute computational models and associated data in standard formats. They support necessary management tasks, including curation, annotation, search, version control, data visualization etc. to different extents.. BioModels Database implements a native, SQL-based search [5] . An alternative search is the ranked model retrieval [8] . Here, models and their annotations are mapped on pre-defined model features (e. g., model organism, author, biological entity), leading to a characteristic term vector for each model. The properties of this vector are numeric values mostly describing term frequency and inverse document frequency (TF-IDF) [9] . The ranking is determined by the comparison of search terms (i. e. provided keywords) with the extracted characteristic term vector per model. Current approaches are solely capable of comparing a set of keywords against an indexed corpus of models and retrieve matching models. In addition, it is possible to create a characteristic term vector directly from a model and, subsequently, query a corpus by example.. For example, a standard search for the keywords "cell cycle" in BioModels Database retrieves all models in the corpus that are relevant to the term "cell cycle". Together, all models returned by this search can be seen as a new, cell cycle focused, model set (or corpus). The same is possible for keywords such as "apoptosis", "calcium oscillation" or "NF-κB". At this point, we end up with different sets of thematically related models. To characterize such a set and, later on, compare them, features describing this specific model set will be helpful. However, it is problematic to identify suitable characteristics for arbitrary or thematically focused sets of models.. In this paper we present four methods for annotationbased feature extraction from arbitrary sets of SBML models. Our methods build on combinations of existing approaches for feature extraction [10] [11] [12] [13] . We exemplify our methods by comparing the characteristic features of thematic sets to the features of arbitrary sets of SBML models. The thematic sets were extracted from BioModels Database and represent the cell cycle, apoptosis, calcium oscillation, and NF-κB. Concepts, i. e. terms in the ontology, were extracted from three major bio-ontologies used to semantically enrich models (GO, ChEBI, SBO). We argue that our methods contribute to the determination of similarity between sets of SBML models. They also provide statistics on the use of ontology terms in SBML models, and on the relation between ontology terms and models. As a proof of concept, we implemented the four different methods described in Section "Results and discussion" in a prototype application b . We then tested all methods on seven different model sets, which we extracted from BioModels Database.

O B I O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O B O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Thesaurus based automatic keyphrase indexing We propose a new method that enhances automatic keyphrase extraction by using semantic information on terms and phrases gleaned from a domain-specific thesaurus. We evaluate the results against keyphrase sets assigned by a state-of-the-art keyphrase extraction system and those assigned by six professional indexers. Keyphrases represent a brief but precise summary of documents. They are widely used for organizing library holdings and providing thematic access to them. Manual assignment of highquality keyphrases is expensive and time-consuming, therefore automatic techniques are in great demand. There are two existing approaches. In keyphrase extraction, the phrases occurring in the document are analyzed to identify apparently significant ones, on the basis of properties such as frequency and length [1, 3, 4, 7] . In term assignment keyphrases are chosen from a controlled vocabulary of terms, and documents are classified according to their content into classes that correspond to elements of the vocabulary [e.g. 2] . One serious disadvantage of the former approach is that the extracted phrases are often ill formed or inappropriate. The assignment approach circumvents this problem, but for satisfactory results a vast and accurate manually created corpus of training material is needed. This paper describes keyphrase indexing, an intermediate approach between keyphrase extraction and term assignment that combines the advantages of both and avoids their shortcomings.. The new keyphrase indexing algorithm, called KEA++, because it improves the original keyphrase extraction algorithm KEA, is based on machine learning and works in two main stages: candidate identification, which identifies thesaurus terms that relate to the document's content, and filtering, which uses a learned model to identify the most significant terms based on certain properties or "features." This paper has presented an algorithm for thesaurus-based indexing of documents, called KEA++. This new approach to keyphrase indexing uses a machine learning technique and semantic information about terms encoded in a structured controlled vocabulary. The main advantage over conventional keyphrase extraction is the use of a controlled vocabulary, which eliminates the occurrence of meaningless or obviously incorrect phrases, and also yields a dramatic improvement in performance, as shown above. The main advantage over conventional term assignment, which already uses a controlled vocabulary, is a dramatically lowered requirement for training data. Performance is independent of the size of the controlled vocabulary, and all experiments have been conducted with just 180 training documents.. Further work to adapt the system to other structured indexing vocabularies and other domains would be an interesting extension of the project.

O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


A Comprehensive Instrument for Measuring Individual Competency of IT Applications in an Enterprise IT Environment An instrument that can efficiently measure individual competency of IT applications (ICITA) is presented. It allows an organization to develop and manage the IT application capability of individuals working in an enterprise IT environment. The measurement items are generated from the definition and major components of individual competency of IT applications. The reliability and validity of the instrument construct are verified by factor and correlation analysis. A 15-item instrument is proposed to efficiently measure individual competency of IT applications and the instrument will contribute to the improved ICITA of human resources working in an enterprise IT environment. key words: individual competency, IT applications, measurement item, measurement instrument Progress of information technology (IT) has made that data resources and information systems (IS) are becoming a firm's critical strategic resources [1] . IT capability can help companies surpass their rivals and is becoming one of the most important resources of an enterprise [2] . It is important for human resources operating in an enterprise information environment to effectively execute tasks by applying their IT resources to their business [3] , [4] . An individual needs to exploit IT applications to efficiently perform his or her direct tasks. An individual IT application directly influences the individual task performance and competitiveness of the organization in an IT environment.. Firms have implemented their IT resources to increase individual business performance and to improve their competitiveness [5] , [6] . Since users have to efficiently utilize IT resources to achieve these objectives, they need sufficient IT competency [7] . Management Information Systems (MIS) researchers point out that adequate understanding of individual IT tools and users who are motivated to use them will lead to realization of the full potential of users' IT applications [7] , [8] . Consequently, developing an instrument to measure the competence of IT users is an important issue in related research [9] , [10] .. Previous studies have focused on specific software skills, professional skills and operational skills, etc. [7] . In order to effectively execute individual tasks in an enterprise IT environment, the individual has to be qualified not with fragmentary IT skills but with total IT capability [11] . The standards of IT skills framework like ITTS and UISS (Japan), SFIA and e-CF (European Union), and FITness (United State of America), were also focused on IT knowledge and IT skills for IT engineers and IT professionals. They did not approach in terms of an entire individual capability of IT applications and only focused on IT knowledge and technical skills. In South Korea, the practical measurement tool like e-Test and certificates of computer utilization capability for an individual also was developed in terms of IT knowledge and skills. But we would like to develop a comprehensive instrument that can measure an entire individual capability of IT application from IT mind to IT potential capability in this study. Individual competency of IT applications (ICITA) means the total capability of an individual to efficiently apply IT resources to his or her business tasks in an enterprise IT environment. A reliable measurement instrument of ICITA may have several advantages. First, it can measure the total IT capability of an individual. Second, the ICITA can be developed systematically according to the measurement results. Third, it can gauge the core capability directly connected with individual business performance, by measuring individual IT capability in terms of competency. Finally, it incorporates IT attitudes into IT experience based on individual's IT capability. Therefore, this study presents an instrument to measure the individual competency of IT applications. It focuses on the total IT capability of an individual to efficiently utilize IT knowledge, solutions and applications, and information systems for his or her tasks in an enterprise IT environment. This study successfully presents a specified ICITA construct, and conceptualizes and operationalizes it. We purify the ICITA instrument and show that the resulting refinement is a concise multi-item scale with relevant reliability and validity. We also illustrates many facets contributing to ICITA including IT attitudes, IT knowledge, IT skills and IT experience. The crucial contributions of our research are threefold. First, this study presents a framework which describes the primary dimensions of ICITA and can be applied to comparative analysis of results from a variety of industries and business departments. Second, we successfully transforms this framework into a validated instrument for measuring ICITA, provides a measurement tool for it, and suggests directions and methods for practitioners to improve it. Third, managers might be able to utilize the ICITA instrument as a different measure of IT values and an indicator of future IT success. Generally, an individual competency of IT applications influences his or her business department execution and further the firm's performance [11] .. Based on these findings, we can suggest several alternatives for ICITA management. Our research developed an alternative measure of ICITA. Our instrument was developed in terms of the total IT capability that needs to efficiently execute the given tasks in an enterprise IT environment. It was verified by a pilot test for human resources working in a variety of industries and firms of IT environment. That is, the instrument was developed in terms of an entire IT application capability for human resources working in a firm IT environment. Firms can utilize ICITA instrument scores as an indicator of ICITA in order to improve and manage the IT application competency of their employees, because it is highly related to overall individual business execution capability in an enterprise IT environment. It is a surrogate variable of ICITA success. Firms can establish an alternative means to effectively develop and improve the ICITA of their employees based on the measurement results from the developed instrument.. Firms can utilize the 15-item ICITA instrument to extract the relative importance of the four factors (i.e., IT attitudes, IT knowledge, IT skills and IT experience) in order to efficiently improve the ICITA of their employees. They can calculate the scores of each factor from the overall ICITA instrument scores. Based on the measurement scores for each ICITA factor, managers can prioritize decisions and actions for improving ICITA factors with low scores. They can efficiently improve and manage ICITA on an organizational level by analyzing demographics such as gender, age, position and education level. Firms can offer personalized improvement plans for their employees based on the subdimensional scores of the ICITA instrument.. This study presented an ICITA instrument that is applicable across industries and business departments. It reports a fundamental framework with descriptions of each of the four ICITA dimensions. Future research can adapt or modify it to fit the characteristics of particular research contexts. We also argue that the availability of the ICITA instrument can stimulate future work on ICITA as well as its antecedents and consequences.. Although the ICITA instrument has passed rigorous validation procedures, our research has several limitations. Although exploratory factor analysis has been performed to examine the ICITA construct, a confirmatory analysis with a larger sample might be necessary for further validation. Researchers could also explore casual models consisting of antecedents and consequences of ICITA using structural equation modeling (SEM) to investigate upstream and downstream factors, such as the effects of ICITA on the business execution capability and performance of users. Finally, this study will contribute to improving the ICITA of human resources that is required to efficiently execute the individual given tasks in an enterprise IT environment. Based on the definition and four components of ICITA, we first generates 26 items to measure ICITA in an enterprise IT environment [7] , [9] , [15] , [18] - [20] . The items were developed from previous literature and were reviewed by about 30 IT experts at our ITRC (IT research center): postdoctoral researchers, professors and IT developers and practitioners. Because there are no widely accepted definitions of the ICITA construct, an exploratory study was utilized to determine the measurement items from a review of the literature and proposals by experts. Comments from experts were reflected in the questions included in the questionnaire survey. These comments enabled us to verify that respondents understood the items and it facilitated instrument refinement and improved focus. Experts noticed that the list of measurement items was generally complete. The refined 26 items we developed are provided in Appendix. Items were unsorted and no sub-headings were used. A global measure of ICITA was included to serve as a criterion. The measurement questionnaire used a five-point Likert-type scale; where the scores of 1-5 denote the following: (1) not at all, (2) a little, (3) moderately, (4) greatly and (5) a great deal. The questionnaire is composed of two response domains: one is the collected demographic data of respondents, such as degree, age, gender, major field, industry and business department, business position level and years of job experience; the other is the response to the measurement items. We collected data from a variety of industries and firms so that the results could be generalized. Thirty medium and large-size firms in the Republic of Korea were contacted and the participation of their workers was requested. Once a firm agreed to cooperate, research assistants directly contacted their workers, described the project objectives, and left our questionnaires for them to complete. The respondents either directly mailed back the completed questionnaires or research assistants collected them one-two weeks later. Over one-third of the firms contacted agreed to participate in the project. The collected questionnaires represented about 46% of the respondents.

O O O O O B I O B I O O O O O O O O O O O B I O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O B I O O O O O O O O O O O O O O O O O O O O O O O B I O B I O O O O O O O O O O O O O O O O O O O O B I B I B I B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O B I O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Geometric Alignment of 2D Gel Electrophoresis Images Abstract. A key technique for protein analysis is the geometric alignment of 2D gel electrophoresis (2-DE) images. We introduce a new hybrid elastic registration approach for 2-DE images, which is based on analytic solutions of the Navier equation. With this approach cross-effects in elastic deformations can be handled, which is important for the registration of 2-DE images. We have successfully applied our approach to register 2-DE gel images of different levels of complexity and have performed a quantitative evaluation of the results. We have also performed a comparison with a previous hybrid elastic registration scheme. 2D gel electrophoresis (2-DE) is the method of choice for analyzing protein expression in the field of proteomics. By this technique a very large number of proteins can easily and simultaneously be separated, identified, and characterized. This is important for understanding protein function. 2-DE separates proteins based on their electrical charge and molecular mass resulting in a 2D array of dark spots (proteins) on a bright background (Fig. 1) . Often a reference population is compared with a test population to analyze the effect of medication.. To accurately and quantitatively compare the generated 2D protein profiles, three main image analysis steps are required, namely, (1) geometric alignment of 2-DE images, (2) detection of spots, and (3) quantification of spots (e.g., shape, contrast). For a general overview we refer to [1] . In this work, we focus on the geometric alignment of 2-DE images. The core task is to find an optimal geometric transformation between image data, which is known as image registration. Due to complex physical and chemical processes the locations of proteins generally vary in different 2-DE images and therefore nonrigid or Elastic registration schemes have to be applied (for a survey see, e.g., [2] ). Severe problems in the case of 2-DE images are that the spot shapes are largely different, that certain spots do not appear in corresponding images, and that spots may smear over a larger area as well as overlap each other.. Previous work on 2-DE image registration can be classified into landmarkbased and intensity-based schemes. Landmark-based schemes first extract landmarks from the images and then compute a transformation based on these features (e.g., [3] ). With intensity-based schemes the image intensities are directly exploited to compute the transformation (e.g., [4] ). Moreover, hybrid approaches that combine landmark-based and intensity-based methods have been proposed, which allow to combine advantages of both types of methods (e.g., [5, 6, 7] ). However, with these approaches only coarse physical deformation models have been used, for example, based on thin-plate splines [7] or clamped-plate splines [6] , or using a Gaussian function for regularization of the deformation field [5] .. In this contribution, we introduce an approach for the registration of 2-DE images, which is based on an improved physical deformation model using analytic solutions of the Navier equation. In contrast to previous spline-based approaches for the registration of 2-DE images (e.g., [5, 6, 7] ), with this approach cross-effects in elastic deformations can be handled, which is important in the case of 2-DE images. Moreover, our approach allows to include landmark correspondences to aid the registration in regions which are difficult to register using intensity information alone. In contrast to [8] where brain images have been registered, we here use a different energy functional where landmark correspondences are directly incorporated instead of requiring an additional deformation field. Applying our elastic registration approach without using landmarks, we achieved good overall registration results for all considered 2-DE images. Only in some regions, in particular, regions with a large number of tiny spots or regions located at the image border, the results are worse compared to other regions. However, by inclusion of a relatively small number of landmarks the registration accuracy could be significantly improved in the respective regions. Moreover, we have quantitatively evaluated the registration result. For the images of easy complexity (Table 1) 208 spots should ideally match. Applying the new registration scheme and using only intensity information, we obtain 200 correctly matched spots (8 incorrectly matched) which calculates to 96.2% correct matches. In contrast, the previous approach in [5] yields only 187 correctly matched spots (21 incorrectly matched), and a pure affine approach is much worse (80 incorrectly matched). By additionally incorporating landmarks, the performance of the new approach improves, i.e., only 5 spots are incorrectly matched. Applying the approach in [5] using additional landmarks yields 7 incorrectly matched, i.e., the result is improved but worse compared to the new approach. For the images of medium complexity we obtained comparable results (Table 2) . From Tables 1 and 2 it can be seen that both elastic approaches yield quite good results. However, it also turned out that for the previous approach [5] the use of additional landmark information is crucial to achieve satisfactory matching results of 96.6% and 94.3%. In contrast, the new approach achieves this level of accuracy without including landmarks, and yields even better results when landmark information is used (97.6% and 96.8%). Therefore, the new approach is well suited in a fully automatic setting and the performance can further be improved when landmark correspondences are available. Moreover, by comparing the resulting deformation grids of both elastic approaches we found that the new approach yields more realistic deformations, in particular, distortions leading to spot smearing as in the case of using [5] are reduced. As an example, Fig. 1 shows a section (384 × 384 pixels) of the registered images for both elastic approaches for images of easy complexity. It can be seen that the new approach (d) yields a registration result without significant distortions. In contrast, the previous approach [5] yields distortions leading to significant smearing, for example, see the bottom right in (c).. In summary, we introduced a new hybrid elastic registration approach for the geometric alignment of 2-DE gel images. With this approach cross-effects in elastic deformations can be handled, which is important for the registration of 2-DE images. We have successfully applied our approach to register 2-DE gel images of different levels of complexity and we found that the approach is superior to a previous hybrid scheme. We have applied the new hybrid registration approach to register 2D polyacrylamide gel electrophoresis images of three different levels of complexity (easy, medium, and difficult). The images are courtesy of Prof. G-Z. Yang, Royal Society/Wolfson MIC Laboratory, Dept. of Computing, Imperial College of Science, Technology, and Medicine, London/UK. In each case, gel images are compared from a reference group with those from a test group [4] . All images represent human protein expressions and have a size of 1024 × 1024 pixels.. To analyze the performance of our approach, we have carried out a quantitative evaluation of the registration results. An obvious measure for the registration accuracy is the number of correctly matched spots. However, note that counting the spots is a non-trivial task in the case of 2-DE images, and also tedious and time consuming. Based on spot counting we obtain the overall number of spots that should ideally match as well as the correctly and incorrectly matched spots. The quantitative evaluation has been performed for images of easy and medium complexity. Tables 1 and 2 show the resulting number of correctly matched spots, the number of incorrectly matched spots, and the fraction of correct matches. Table 1 . Quantitative evaluation results for images of easy complexity (208 ideally matching spots) using affine registration, a previous elastic registration approach [5] , and the new approach: Number of correctly (ncorrect) and incorrectly (nincorrect) matched spots as well as fraction of correct matches Approach Information ncorrect nincorrect Correct Affine [10]

O O O O B I I O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O B I O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Electrochromic organic and polymeric materials for display applications An electrochromic material is one where a reversible color change takes place upon reduction (gain of electrons) or oxidation (loss of electrons), on passage of electrical current after the application of an appropriate electrode potential. In this review, the general field of electrochromism is introduced, with coverage of the types, applications, and chemical classes of electrochromic materials and the experimental methods that are used in their study. The main classes of electrochromic organic and polymeric materials are then surveyed, with descriptions of representative examples based on the transition metal coordination complexes, viologen systems, and conducting polymers. Examples of the application of such organic and polymeric electrochromic materials in electrochromic displays are given. q Numerous chemical materials exhibit redox states with distinct electronic (UV/visible) absorption spectra. Where the switching of redox states generates new or different visible region bands, the material is said to be electrochromic [1] [2] [3] [4] . Color changes in an object give visual signals that can be used to convey useful information to an observer [1] . Furthermore, by selective absorption or transmission of light by a material, the light energy impinging upon an observer can be modulated [1] . Where a chemical or physical external stimulus causes a reversible color change or variation in light transmission, the possible applications are considerable. For such systems, color change phenomena are classified [1] after the stimulus that causes the change, such as electrochromism, photochromism, thermochromism and gasochromism. An electrochromic material is one where a reversible color change takes place upon reduction (gain of electrons) or oxidation (loss of electrons), on passage of electrical current after the application of an appropriate electrode potential [2] [3] [4] [5] [6] [7] [8] [9] [10] .. Many chemical species can be switched between redox states that have distinct electronic absorption spectra. Such spectra arise from either a moderate energy internal electronic excitation or an intervalence optical charge transfer where the chemical species has two centers of differing valence or oxidation state [2] [3] [4] [5] [6] [7] [8] [9] [10] . While materials are considered to be electrochromic when marked visible color changes are shown under illumination, recent interest in electrochromic devices (ECDs) for multispectral energy modulation by reflectance and absorbance has extended the definition [11] . Chemical species are now being studied for modulation of radiation in the near infrared (NIR) [10, 12] , thermal infrared [13] , and microwave regions, and 'color' can mean response of detectors to these electromagnetic regions, not just the human eye [11] .. Transition metal coordination complexes are potentially useful as electrochromic materials because of their intense coloration and redox reactivity [10, 30] . Chromophoric properties arise from low-energy metal-to-ligand charge transfer (MLCT), intervalence CT, intraligand excitation, and related visible region electronic transitions. Because these transitions involve valence electrons, chromophoric characteristics are altered or eliminated upon oxidation or reduction of the complex. Any colored transition metal coordination complex that is redox-switchable within the 'potential window' of a given electrolyte solution will undergo an accompanying color change and will therefore be electrochromic, at least to some extent. While these spectroscopic and redox properties alone would be sufficient for direct use of transition metal coordination complexes in solution-phase ECDs, polymeric systems based on coordination complex monomer units, which have potential use in all-solid-state systems, are frequently investigated.. Electrochemical polymerization is often used to prepare redox active polymer films on electrode surfaces [31] . This technique has the advantage that a wide variety of conducting substrates can be used, and that film thickness can be directly controlled by the electrochemical potential scan rate, the potential range, polymerization time and the choice of monomer concentration and electrolyte solution.. Salts of quaternized 4,4 0 -bipyridine are herbicides and are manufactured on a large scale [15] . The ready availability of 4,4 0 -bipyridine and the ease of varying the nature of the quaternizing agent have allowed intensive research into the electrochromic properties of such 'viologens' [15] . The prototype viologen, 1,1 0 -di-methyl-4,4 0 -bipyridilium, is known as methyl viologen (MV), with other simple symmetrical bipyridilium species being named 'substituent' viologen. Of the three common viologen redox states ( Fig. 4) , dication is the most stable and is colorless when pure unless optical charge transfer with the counter anion occurs. Reductive electron transfer to the viologen dication forms the radical cation, the stability of which is attributable to the delocalisation of the radical electron throughout the p-framework of the bipyridyl nucleus, the 1 and 1 0 substituents commonly bearing some of the charge.. The viologen radical cations are intensely colored, with high molar absorption coefficients, owing to optical charge transfer between the (formally) C1 and zero valent nitrogens. Suitable choice of nitrogen substituents in viologens to attain the appropriate molecular orbital energy levels can, in principle, allow color choice of the radical cation. For example, alkyl groups promote a blue/violet color whereas the radical cation of 1,1 0 -bis(4-cyanophenyl)-4,4 0bipyridilium (cyanophenyl paraquat, 'CPQ') [50] in acetonitrile has an intense green color (83,300 dm 3 mol K1 cm K1 at the l max (674 nm)). The intensity of the color exhibited by di-reduced viologens ( Fig. 4 ) is low since no optical charge transfer or internal transition corresponding to visible wavelengths is accessible.. The first electrochromic display using viologens was reported by Schoot et al. [51] (of the Philips Laboratories) in 1973. Philips had submitted Dutch patents in 1970 [52] for 1,1 0 -diheptyl-4,4 0 -bipyridilium as the electrochromic species, while in 1971 ICI patented the use of cyanophenyl paraquat [53] . At this time, other displays based on heptyl viologen were being investigated by Barclay's group at Independent Business Machines (IBM) [54] , and by Texas Instruments in Dallas, although their work was not published until after their program was discontinued [55] . A 64!64 pixel integrated display with eight levels of gray tone on a 1-in 2 . silicon chip, capable of giving quite detailed images, was reported [56] . It is likely that these displays were not exploited further owing to LCD competition, although they may still have a size advantage in large area devices.. 'Paper-quality' railway termini information long-term data displays are now close to commercialization, using a new type of nano-structured electrochromic organic/inorganic hybrid system, where electrochromic groups such as phosphonated viologens and phenothiazine molecules are attached to the rough surface of a very high surface area porous oxide film [57, 58] . Typically, such films consist of networks of interconnected semi-conducting or conducting metal oxide nanocrystals, deposited onto an optically transparent conducting glass electrode. On applying a negative potential, electrons are injected into the conduction band of the semi-conductor and the absorbed molecule is reduced and changes color. Applying a positive potential reverses the process.. Whilst not a display device, it is of interest to note Gentex's commercialized automatic-dimming interior 'Night Vision Safety' (NVS) mirror that employs viologen electrochromism [8] . In this system, which functions wholly by solution electrochromism, an ITO-glass surface (conductive side inwards) and the reflective metallic surface, spaced a fraction of a millimeter apart, form the two electrodes of the cell, with a solvent containing two electroactive chemical species that function both as electrochromic materials and supporting electrolyte. Two electroactive chemical species comprise a substituted (cationic) viologen, which serves as the cathodic-coloring electrochromic species, and a negatively charged (possibly) phenylene diamine as the anodically coloring electrochromic material. After switching the mirror on, the species migrate to their respective electrodes. Once the dual electrochromic coloration process has begun, the products will diffuse away from their respective electrodes and meet in the intervening solution, where a mutual reaction regenerating the original uncolored species takes place. This type of electrochromic device therefore requires application of a continuous small current for replenishment of the colored electroactive species lost by their mutual redox reaction in solution. Bleaching occurs at short or open circuit by homogeneous electron transfer in the bulk of the solution. Although not an electrochromic phenomenon, the ingenious control system for this device is noteworthy. A photosensitive detector is placed facing rearward to monitor any dazzling incident light. However, this would also be triggered in daylight, resulting in an unwanted darkening of the mirror. This problem is avoided by a second forwardlooking detector, which, on seeing daylight, is programed to cancel any operation of the controlling sensor, which therefore only responds at night.. Chemical or electrochemical oxidation of numerous resonance-stabilized aromatic molecules, such as pyrrole, thiophene, aniline, furan, carbazole, azulene, indole, and others, produces electronically conducting polymers [2, [17] [18] [19] [69] [70] [71] . The polymerization is believed to involve either radical-cation/radical-cation coupling or reaction of a radical-cation with a neutral monomer. The mechanism of electropolymerization of the five-membered heterocycle, pyrrole, with radical-cation/radical-cation coupling is shown in Fig. 6 .. After loss of two protons and re-aromatization, the dimer forms from the di-hydro dimer dication. The dimer (and succeeding oligomers) is more easily oxidized than the monomer and the resulting dimer radical cation undergoes further coupling reactions, proton loss and rearomatization. Electropolymerization proceeds through successive electrochemical and chemical steps according to a general E(CE) n scheme, until the oligomers become insoluble in the electrolyte solution and precipitate onto the electrode surface [71] . In this manner, high-quality oxidized conducting films can be formed directly.. In the oxidized state, conducting polymers are chargebalanced, 'doped', with counter anions ('p-doping') and have a delocalized p-electron band structure [71] . Reduction of 'p-doped' conducting polymers, with concurrent counter anion exit (or electrolyte cation incorporation), removes the electronic conjugation to give the 'undoped' (neutral) electrically insulating form. The energy gap (E g , electronic bandgap) between the highest occupied p-electron band (valence band) and the lowest unoccupied band (the conduction band) determines the intrinsic optical properties of these materials. This is illustrated in Fig. 7 with polypyrrole once again as an example. In some instances, the 'undoped' neutral state can undergo reductive cathodic 'doping', with cation insertion ('n-doping') to balance the injected charge. However, the stability of the negatively charged polymer state is limited and n-doping is more difficult to achieve. It is to be noted that the 'p-doping' and 'n-doping' nomenclature comes from classical semi-conductor theory. The supposed similarity between conducting polymers and doped semiconductors arises from the manner in which the redox charges in the polymer change its optoelectronic properties. In fact, the suitability of the terms 'doping' and 'dopant' has been criticized when referring to the movement of counter ions and electronic charge through these polymers because true doping involves small (classically sub ppm) amounts of dopant. However, terms such as 'doping' are now so widely used that additional, new terminology might confuse.. All conducting polymers are potentially electrochromic, redox switching giving rise to new optical absorption bands in accompaniment with simultaneous transport of electronic charge and counter ions in the polymer matrix. Oxidative p-doping shifts the optical absorption band towards the lower energy part of the spectrum. The color change or contrast between doped and undoped forms of the polymer depends on the magnitude of the bandgap of the undoped polymer. Thin films of conducting polymers with E g greater than 3 eV (w400 nm) are colorless and transparent in the undoped form, while in the doped form they are generally absorbing in the visible region. Those with E g equal to or less than 1.5 eV (w800 nm) are highly absorbing in the undoped form but, after doping, the free carrier absorption is relatively weak in the visible region as it is transferred to the near infrared. Polymers with intermediate gaps have distinct optical changes throughout the visible region and can be made to induce many color changes. The field of electrochromism is rapidly expanding both in terms of the range of electrochromic systems that has been reported and the novel commercial applications that are being proposed. In the case of organic and polymeric electrochromic materials for display applications, a number of representative examples have been described in this article. Tailoring the color of electrochromic polymers remains a particularly active research area. Although not described here, in addition to the synthesis of novel functionalized monomers and use of composites, other chemical and physical methods are investigated for the control of the perceived color of electrochromic polymers. Methods include the use of polymer blends, laminates and patterning using screen and ink-jet printing [135] . Analysis of ECD color changes is now routinely measured by spectrocolorimetry using Commission Internationale de l'Eclairage (CIE) (x,y)-chromaticity coordinates. This method is useful for the comparison of the electrochemical and optical properties of conjugated polymers, and for gaining control of the color of dual polymer electrochromic devices [136, 137] . By controlling the electron density and steric interactions along conjugated polymer backbones, a set of electrochromic polymers that provide colors through the full range of color space has been developed through the study of 12 electrochromic polymers [136] .

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Graph

Rigidity,

Cyclic

Belief

Propagation,

and

Point

Pattern

Matching

A

recent

paper

proposed

a

provably

optimal

polynomial

time

method

for

performing

near-isometric

point

pattern

matching

by

means

of

exact

probabilistic

inference

in

a

chordal

graphical

model.

Its

fundamental

result

is

that

the

chordal

graph

in

question

is

shown

to

be

globally

rigid,

implying

that

exact

inference

provides

the

same

matching

solution

as

exact

inference

in

a

complete

graphical

model.

This

implies

that

the

algorithm

is

optimal

when

there

is

no

noise

in

the

point

patterns.

In

this

paper,

we

present

a

new

graph

that

is

also

globally

rigid

but

has

an

advantage

over

the

graph

proposed

in

Its

maximal

clique

size

is

smaller,

rendering

inference

significantly

more

efficient.

However,

this

graph

is

not

chordal,

and

thus,

standard

Junction

Tree

algorithms

cannot

be

directly

applied.

Nevertheless,

we

show

that

loopy

belief

propagation

in

such

a

graph

converges

to

the

optimal

solution.

This

allows

us

to

retain

the

optimality

guarantee

in

the

noiseless

case,

while

substantially

reducing

both

memory

requirements

and

processing

time.

Our

experimental

results

show

that

the

accuracy

of

the

proposed

solution

is

indistinguishable

from

that

in

when

there

is

noise

in

the

point

patterns.

POINT

pattern

matching

is

a

fundamental

problem

in

pattern

recognition

and

has

been

modeled

in

several

different

forms

depending

on

the

demands

of

the

application

domain

in

which

it

is

required

A

classic

formulation

that

is

realistic

in

many

practical

scenarios

is

that

of

near-isometric

point

pattern

matching,

in

which

we

are

given

both

a

"template"

ðT

Þ

and

a

"scene"

ðSÞ

point

pattern,

and

it

is

assumed

that

S

contains

an

instance

of

T

(say,

T

apart

from

an

isometric

transformation

and

possibly

some

small

jitter

in

the

point

coordinates.

The

goal

is

to

identify

T

in

S

and

find

which

points

in

T

correspond

to

which

points

in

T

Recently,

a

method

was

introduced

that

solves

this

problem

efficiently

by

means

of

exact

belief

propagation

in

a

certain

graphical

model

The

approach

is

appealing

because

it

is

optimal

not

only

in

that

it

consists

of

exact

inference

in

a

graph

with

small

maximal

clique

size

(¼

for

matching

in

IR

but

also

in

that

the

graph

itself

is

optimal.

There

it

is

shown

that

the

maximum

a

posteriori

(MAP)

solution

in

the

sparse

and

tractable

graphical

model

where

inference

is

performed

is

actually

the

same

MAP

solution

that

would

be

obtained

if

a

fully

connected

model

(which

is

intractable)

could

be

used.

This

is

due

to

the

so-called

global

rigidity

of

the

chordal

graph

in

question:

When

the

graph

is

embedded

in

the

plane,

the

lengths

of

its

edges

uniquely

determine

the

lengths

of

the

absent

edges

(i.e.,

the

edges

of

the

graph

complement)

The

computational

complexity

of

the

optimal

point

pattern

matching

algorithm

is

then

shown

to

be

Oðnm

Þ

(both

in

terms

of

processing

time

and

memory

requirements),

where

n

is

the

number

of

points

in

the

template

point

pattern

and

m

is

the

number

of

points

in

the

scene

point

pattern

(usually

with

m

n

in

applications).

This

reflects

precisely

the

computational

complexity

of

the

Junction

Tree

algorithm

in

a

chordal

graph

with

OðnÞ

nodes,

OðmÞ

states

per

node,

and

maximal

cliques

of

size

The

authors

present

experiments

which

give

evidence

that

the

method

substantially

improves

on

well-known

matching

techniques,

including

Graduated

Assignment

In

this

paper,

we

show

how

the

same

optimality

proof

can

be

obtained

with

an

algorithm

that

runs

in

Oðnm

Þ

time

per

iteration.

In

addition,

memory

requirements

are

precisely

decreased

by

a

factor

of

m.

We

are

able

to

achieve

this

by

identifying

a

new

graph,

which

is

globally

rigid

but

has

a

smaller

maximal

clique

size:

three.

The

main

problem

we

face

is

that

our

graph

is

not

chordal,

so

in

order

to

enforce

the

running

intersection

property

for

applying

the

Junction

Tree

algorithm,

the

graph

should

first

be

triangulated;

this

would

not

be

interesting

in

our

case,

since

the

resulting

triangulated

graph

would

have

larger

maximal

clique

size.

Instead,

we

show

that

belief

propagation

in

this

graph

converges

to

the

optimal

solution,

although

not

necessarily

in

a

single

iteration.

In

practice,

we

find

that

convergence

occurs

after

a

small

number

of

iterations,

thus

improving

the

runtime

by

an

order

of

magnitude.

We

compare

the

performance

of

our

model

to

that

in

with

synthetic

and

real

point

sets

derived

from

images

and

show

that

in

fact

comparable

accuracy

is

obtained

while

substantial

speedups

are

observed.

We

have

shown

that

the

near-isometric

point

pattern

matching

problem

can

be

solved

much

more

efficiently

than

what

is

currently

reported

as

the

state

of

the

art,

while

maintaining

the

same

optimality

guarantees

for

the

noiseless

case

and

comparable

accuracy

for

the

noisy

case.

This

was

achieved

by

identifying

a

new

type

of

graph

with

the

same

global

rigidity

property

of

previous

graphs,

in

which

exact

inference

is

far

more

efficient.

Although

exact

inference

is

not

directly

possible

by

means

of

the

Junction

Tree

algorithm

since

the

graph

is

not

chordal,

what

we

managed

to

show

is

that

loopy

belief

propagation

in

such

a

graph

does

converge

to

the

optimal

solution

in

a

sufficiently

small

number

of

iterations.

In

the

end,

the

advantage

of

the

smaller

clique

size

of

our

model

dominates

the

disadvantage

caused

by

the

need

for

more

than

a

single

iteration.

We

consider

point

matching

problems

in

IR

The

problem

we

study

is

that

of

near-isometric

point

pattern

matching

(as

defined

above),

i.e.,

one

assumes

that

a

near-isometric

instance

ðT

Þ

of

the

template

ðT

Þ

is

somewhere

"hidden"

in

the

scene

ðSÞ.

By

"near-isometric,"

it

is

meant

that

the

relative

distances

of

points

in

T

are

approximately

preserved

in

T

For

simplicity

of

exposition,

we

assume

that

T

T

and

S

are

ordered

sets

(their

elements

are

indexed).

Our

aim

is

to

find

a

map

x

T

S

with

image

T

that

best

preserves

the

relative

distances

of

the

points

in

T

and

T

i.e.,.

where

DðT

Þ

is

the

matrix

whose

ði;

jÞth

entry

is

the

euclidean

distance

between

points

indexed

by

i

and

j

in

T

and

k

Á

k

is

the

Frobenius

norm.

Note

that

finding

x

Ã

is

inherently

a

combinatorial

optimization

problem

since

T

is

itself

a

subset

of

S,

the

scene

point

pattern.

In

a

generic

point

in

T

is

modeled

as

a

random

variable

ðX

i

Þ

and

a

generic

point

in

S

is

modeled

as

a

possible

realization

of

the

random

variable

ðx

i

Þ.

As

a

result,

a

joint

realization

of

all

the

random

variables

corresponds

to

a

match

between

the

template

and

the

scene

point

patterns.

A

graphical

model

(see

and

is

then

defined

on

this

set

of

random

variables

whose

edges

are

set

according

to

the

topology

of

a

socalled

graph

(any

that

spans

T

A

is

a

graph

obtained

by

starting

with

the

complete

graph

on

three

vertices,

K

and

then

adding

new

vertices

that

are

connected

only

to

those

same

three

vertices.

Fig.

shows

an

example

of

a

it

should

be

noted

that

the

points

in

the

template

set

correspond

to

the

nodes

in

this

graph,

whereas

the

points

in

the

scene

correspond

to

their

assignments.

The

reasons

claimed

in

for

introducing

as

a

graph

topology

for

the

probabilistic

graphical

model

are

that

are

globally

rigid

in

the

plane

and

are

chordal

graphs.

This

implies

that

the

model

is

"optimal"

(in

a

way

that

will

be

made

clear

in

Section

in

the

context

of

the

new

graph

we

propose)

and

that

have

a

Junction

Tree

with

fixed

maximal

clique

size

ð¼

as

a

result,

it

is

possible

to

perform

exact

inference

in

polynomial

time

Potential

functions

are

defined

on

pairs

of

neighboring

nodes

and

are

large

if

the

difference

between

the

distance

of

neighboring

nodes

in

the

template

and

the

distance

between

the

nodes

they

map

to

in

the

scene

is

small

(and

small

if

this

difference

is

large).

This

favors

isometric

matchings.

More

precisely,.

where

fðÁÞ

is

typically

some

unimodal

function

peaked

at

zero

(e.g.,

a

zero-mean

Gaussian

function)

and

dðÁ;

ÁÞ

is

the

euclidean

distance

between

the

corresponding

points

(for

simplicity

of

notation,

we

do

not

disambiguate

between

random

variables

and

template

points

or

realizations

and

scene

points).

For

the

case

of

exact

matching,

i.e.,

when

there

exists

an

x

Ã

such

that

the

minimal

value

in

is

zero,

then

fðÁÞ

¼

ðÁÞ

(where

ðÁÞ

is

just

the

indicator

function

ðÁÞ).

The

potential

function

of

a

maximal

clique

ðÉÞ

is

then

simply

defined

as

the

product

of

the

potential

functions

over

its

six

ð¼

C

Þ

edges

(which

will

be

maximal

when

every

factor

is

maximal).

It

should

be

noted

that

the

potential

function

of

each

edge

is

included

in

no

more

than

one

of

the

cliques

containing

that

edge..

For

the

case

of

exact

matching

(i.e.,

no

jitter),

it

is

shown

in

that

running

the

Junction

Tree

algorithm

on

the

graphical

model

with

fðÁÞ

¼

ðÁÞ

will

actually

find

a

MAP

assignment

which

coincides

with

x

Ã

i.e.,

such

that

DðT

Þ

À

Dðx

Ã

ðT

ÞÞ

k

k

¼

This

is

due

to

the

"graph

rigidity"

result,

which

tells

us

that

equality

of

the

lengths

of

the

edges

in

the

and

the

edges

induced

by

the

matching

in

T

is

sufficient

to

ensure

the

equality

of

the

lengths

of

all

pairs

of

points

in

T

and

T

This

will

be

made

technically

precise

in

Section

when

we

prove

an

analogous

result

for

another

graph.

O O O B I O B I I O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O