Alain Cucchi
email: alain.cucchi@univ-reunion.fr

Chantal Fuhrer

LIFTING THE VEIL ON ORGANIZATIONAL STRUCTURE: A SOCIAL NETWORK ANALYSIS OF PROFESSIONAL E-MAIL USE

Keywords: Structure, Power, Centrality, Social Network Analysis, IT use, Electronic Mail, Structural Equation Modeling

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INTRODUCTION

In a context of competitive pressure, the importance of designing organizational capacity for handling information processing requirements has been recognized [START_REF] Wang | Effect of the fit between information processing requirements and capacity on organizational performance[END_REF]. While Information Systems (IS) and Technologies (IT) investments are growing rapidly to fill the need for this capacity, an important management question is their effect on the organizational structure and performance [START_REF] Barua | Information Technologies and Business Value: An Analytic and Empirical Investigation[END_REF]. Information technologies are thought to enable decentralization of control and decision-taking by facilitating the dissemination and sharing of information throughout the firm. Complex structures imply more elaborate coordination, control, and communication mechanisms that in turn require more information technology [START_REF] Bergeron | Fit in strategic information technology management research: an empirical comparison of perspectives[END_REF]) E-mail is one of these technologies and is used to improve organizational coordination and communication. Telecommunication use is closely linked to organizational structure and culture [START_REF] Rowe | L'interaction telecommunications -structure des organizations[END_REF][START_REF] Rowe | Cultural values and telecommunication media use[END_REF]. However, unlike workflow technology, it is a versatile technology that does not limit the communication flow between 'actors' (where 'actor' designates a participating member of the organization). Thus, the study of such communication tools may reveal a different structure to the one embedded in the organizational chart. The study of this structure embedded in e-mail relationships is the object of this work.

Based on the data describing organizational e-mail exchanges, this research deals with organizational structure, personal power, and actors' centrality in a network. Social Network Analysis (SNA) is used to study the social relationships embedded in these data. The aim is to discover the way an individual's characteristics and aspects of organizational power may influence actors' centrality in the e-mail network. More precisely, the aim of this paper is:

to compute centrality indexes related to Social Network Analysis to test the relationships between the individual and aspects of organizational power and the network centrality indexes To do so, the first part of this work describes some conceptual aspects. A section is dedicated to the structure and the information processing view of the organization. Another section deals with power and centrality in Social Network Analysis. The second part describes an empirical test of this hypothesis. Data comes from 385 employees, the email users within a group, and from its staff file.

A Structural Equations Modeling (SEM) method is used to test the influence of personal and organizational attributes on indexes of network centrality. Results are discussed and guidelines for future research are described in the conclusion.

STRUCTURE, POWER AND CENTRALITY STRUCTURE AND INFORMATION

"The beginning of administrative wisdom is the awareness that there is no one optimum type of management system," [START_REF] Burns | The management of Innovation[END_REF]. One of the most influential theories in organizational structure literature is the contingency approach. Originally developed by Woodward, Burns and Stalker, this approach considers that many different organizational structures may be adopted to reach a high level of performance. There is no "one best way", one best organizational structure, but different structures which may be used to better fit organizational needs. Thus, the structure is dependent on the organization. In the field of strategy, researchers have looked at the contingency effects of the relationships between the firm's environment, strategy, structure, and information systems [START_REF] Bergeron | Fit in strategic information technology management research: an empirical comparison of perspectives[END_REF].

The structure of a firm is a complex set of goals, functions, and relationships among units that allow an organization to react effectively to market demands.

Factors such as technology, environmental uncertainty, and strategy may affect the organizational structure [START_REF] Woodward | Industrial Organization: Theory and Practice[END_REF][START_REF] Lawrence | Adapter les structures de l'entreprise. Intégration ou différenciation[END_REF][START_REF] Galbraith | Designing complex organizations[END_REF]. The information processing (IP) view of the organization [START_REF] Galbraith | Designing complex organizations[END_REF][START_REF] Galbraith | Organization design[END_REF] combines the decision-making process view of it [START_REF] Simon | Administration et processus de décision[END_REF] with the contingency approach. It considers that organizational information needs vary according to technological, environmental, strategical, and structural contexts. These areas differ in their dynamism, complexity or uncertainty, and the related decisions need differing amounts of information. However, according to the bounded rationality approach, information processing capacity is bounded [START_REF] Simon | Administration et processus de décision[END_REF]. Thus, according to the IP view, a high level of organizational performance can be reached when information processing capacity fits information processing requirements. Although organizational performance measures and concepts of fit are somewhat problematic, several models and methodologies may be used in the measurement assessment [START_REF] Bergeron | Fit in strategic information technology management research: an empirical comparison of perspectives[END_REF][START_REF] Raymond | L'impact des systèmes d'information sur la performance de l'entreprise[END_REF][START_REF] Seddon | A Respecification and Extension of the DeLone and McLean Model of IS Success[END_REF].

From a global point of view, organizational structure is dependent upon the level of coordination, formalization and specialization of organizational tasks [START_REF] Bergeron | Fit in strategic information technology management research: an empirical comparison of perspectives[END_REF]. Two prominent structural dimensions of organizations are centralization and formalization [START_REF] Rapert | Reconsidering organizational structure: A dual perspective of frameworks and processes[END_REF]. Formalization indicates "the extent to which an organization uses rules and procedures to prescribe behavior". This definition is close to that of the standardization concept [START_REF] Mintzberg | Structure et dynamique des organisations[END_REF][START_REF] Kalika | Structures d'entreprises[END_REF]. Centralization represents "the degree to which the right to make decisions and evaluate activities is concentrated" [START_REF] Fredrickson | The strategic decision process and organization structure[END_REF].

The purpose of this paper is to better interpret the centralization dimension by applying SNA to e-mail use. In the IP view of the organization, centralization is related to the information flow and the way it is concentrated. In human interactions, SNA measures the way human relationships are concentrated.

These relationships build a network where actors' positions condition their power.

The assumption of this paper is that e-mail supports human interactions. The idea is to use the centrality measures of the SNA in the e-mail context to better interpret the relationships embedded in this network. To do so, two main concepts need to be described: Power and Centrality.

POWER CONCEPTS AND ASSESSMENTS

IS researchers have had difficulty defining and measuring the theoretical concept of power [START_REF] Jasperson | Power and Information Technology Research: A Metatriangulation Review[END_REF]. Several academic disciplines have studied this concept using a variety of approaches. These interdisciplinary aspects provide a useful perspective, but also bring more difficulties. "The concept of power is as ancient and ubiquitous as any that social theory can boast" [START_REF] Dahl | The Concept of Power[END_REF].

What is power and how can it be assessed? Several definitions of power have been proposed, focusing either on the characteristics of a "powerful actor" or on the relationship between "powerful actors" and others. Most studies of power have focused on hierarchical power, the power of supervisors over subordinates.

Dahl for example defined power as the relations between actors (1957). The power of an actor A is his capacity to get another actor B to do something that B would not otherwise have done. Similar definitions have been given by authors such as [START_REF] Emerson | Power-Dependence Relations[END_REF] or Salancik and Pfeffer (cited by Pfeffer 1981), for whom power is "the ability of those who possess power to bring about the outcomes they desire" [START_REF] Salancik | Who Gets Power -And How They Hold On to it: A Strategic-Contingency Model of Power[END_REF]. However, power is not only hierarchical. According to [START_REF] Crozier | L'acteur et le système[END_REF], power is multiform and one can define the common denominator as the possibility for a person or a group to have an effect on other people or groups. The definition is deliberately simple in order to focus on the main aspect: the relational characteristic of power.

More precisely, power can only spread through exchange between actors engaged in a relationship, which is to say through negotiation.

In a complex organization, the subunits are not equally powerful [START_REF] Pfeffer | Power in Organizations[END_REF]. Therefore, power is also "a structural phenomenon, created by the division of labor and departmentalization that characterize the specific organization or set of organizations being investigated." However, from an organizational point of view, power can be used in the coordination of organizational activities. According to [START_REF] Mintzberg | Structure et dynamique des organisations[END_REF], coordination is the main feature of organizational structure.

Coordination is based on organizational rules and processes that are neither fixed nor imposed by executives. Behind the organizational charts and official rules, a set of tacit and social interactions regulates employee activities. This underground structure embedded in social interactions may affect individual power and organizational efficiency.

Although many definitions of power can be used, it is largely agreed that power characterizes relationships among social actors. As Pfeffer said, "a person is not "powerful" or "powerless" in general, but only with respect to other social actors in a specific social relationship" (1981). Different power approaches are summarized in Table 1.

Table 1: Power Conceptualizations (adapted from [Jasperson et al., 2002, p.400]).

Power as Authority

Hierarchical power, institutional power, organizational power, rational power. Power as Centralization, Decision rights, participation in decision making Disciplinary power, rational power, resource control, sovereign power, systems/structural power, zero sum power.

Power as Influence Behavioral power, interpretive power, network centrality.

The assessment of power requires "the ability to know what would have happened without the intrusion of the power holder" [START_REF] Pfeffer | Power in Organizations[END_REF]. Power assessment is therefore difficult because it requires the measurement of to what extent an actor manages to influence the behavior of others.

However, several authors have proposed some possible power assessments.

Pfeffer's proposition can guide our reflection. He argued that power can be assessed by its determinants, by its consequences, by its symbols, or by reputation indicators [START_REF] Pfeffer | Power in Organizations[END_REF]. Let us examine these four possibilities.

Assessing power by its determinants implies knowing the causes of power. An actor's power is therefore measured by the number of causes possessed [START_REF] Pfeffer | Power in Organizations[END_REF].

Assessing power by its consequences implies knowing, in contested decisions within organizations, which actor benefits and to what extent. The example given by Pfeffer to illustrate this idea is the budget distribution among subunits (1981).

In our case, we must be able to identify which resources or decisions are likely to be determined on the basis of power in an organization. A relevant one is salary, which one can consider as individual budget distribution. Salary is a scarce resource and is usually a source of conflict; we can consider it as a consequence of power. Moreover, the status position of the employee (from the higher status of Director to the lower status of employee) is an indicator of hierarchical power. In this context, the powerful actor will be the one with the higher salary and higher status.

Concerning the assessment of power by its symbols, the idea here is to assess power through the use of symbols of power. Examples given by Pfeffer are titles, special parking places, automobiles, and so on (1981). In our case, the status position of the employee mentioned above, communication tools such as a cellular telephone or an individual phone number can all be considered as symbols of power.

Concerning the reputation indicators of organizational power, the idea is to ask people who the powerful actor is. However, this method may have several biases (See Pfeffer, 1981, p.55 for details.)

Pfeffer's power assessments describe relevant items to measure the actors' level of organizational power. Organizational status, salary level, telephone number, and cellular phone are registered in the management files. They have been chosen to assess the organizational power of an actor in this study.

Jasperson et al. have described an interesting study of power in the area of information technology research [START_REF] Jasperson | Power and Information Technology Research: A Metatriangulation Review[END_REF]. They studied 82 articles which concerned power. Their study shows that more than a quarter of the 82 articles defined power as the ability to influence. This observation is in accordance with the idea of power as a relationship. In this study, the relationships between actors will be assessed through e-mail exchanges. In SNA literature, the structure of the relationship conditions actors' power, and those placed centrally in a network should be more powerful than others. Is it true in the e-mail context? To test this hypothesis, SNA centrality measures need to be described.

CENTRALITY FROM A SOCIAL NETWORK PERSPECTIVE

In his description of managerial work, [START_REF] Mintzberg | The Manager's Job: Folklore and Fact[END_REF] considered that "managers are vested with formal authority over an organizational unit. From formal authority comes status, which leads to various interpersonal relations, and from these comes access to information. Information, in turn, enables the manager to make decisions and strategies for the unit" [START_REF] Mintzberg | The Manager's Job: Folklore and Fact[END_REF].

Managerial work integrates different roles, resulting from formal authority and organizational power. He identified ten roles: three which are interpersonal, three informational, and four decisional. Among these roles, four focus on information processing. In their liaison role, managers link people from the vertical chain of command to people outside their units. In their monitoring role, they perpetually scan the environment for information, questioning liaison contacts and subordinates, and receiving unsolicited information, much of it as a result of the network of personal contacts. In the disseminator role, the manager passes some privileged information directly to subordinates, who would otherwise have no access to it. In the spokesperson role, the manager sends some information to people outside the unit, to the influential people who control the organizational unit. As a result, processing information is a key part of the manager's job and, in large part, communication is their work [START_REF] Mintzberg | The Manager's Job: Folklore and Fact[END_REF]. These roles describe managers as informational brokers and reveal their centrality in the organizational information processing. SNA can be used to assess this centrality.

The social network perspective

SNA is an unusual way to interpret organizational phenomenon and management issues, particularly in the Information Systems domain [START_REF] Cucchi | Etude de la communication par l'Analyse des Réseaux Sociaux; application à la messagerie électronique[END_REF].

Although it has existed for a long time [START_REF] Tichy | Social Network Analysis for Organizations[END_REF], three main reasons have usually been cited to explain why it is so rarely used in the organizational area:(1) an incomplete conceptual framework, (2) specialization of academic disciplines and (3) methodological constraints in considering a large data set [START_REF] Tichy | Networks in organizations[END_REF].

SNA describes a society as a system of participants -individuals, groups, organizations -linked by a variety of relations. Several kinds of link may (or may not) link each pair of participants [START_REF] Tichy | Networks in organizations[END_REF]. A social network is a collection of nodes (people, organizations) linked by a collection of social relations (friendships, payments, etc.) [START_REF] Laumann | Community Structure as Interorganizational Linkages[END_REF]. Network analysis describes the structure and the configuration of these relations. It attempts to identify their causes and consequences [START_REF] Tichy | Networks in organizations[END_REF][START_REF] Laumann | Networks or Collective Action: A Perspective on Community Influence Systems[END_REF][START_REF] Nohria | Introduction: "Is a network perspective a useful way to studying organizations[END_REF]. From a social network perspective, actors interact socially with each other.

This perspective focuses on these interactions (between individuals in groups, among groups within an organization, among groups and individuals performing roles in different organizations, etc.) and allows a better description and understanding of organizational activities [START_REF] Lamb | Reconceptualizing Users as Social Actors in Information Systems Research[END_REF]. Thus, it allows one to take into account both kinds of characteristics: the social actor ones (relative to other actors) and the relational ones which tie each actor to the whole network. Of these, the one that is of interest is an actor's centrality.

Centrality Concepts and assessments

The usual concept of centrality implies the study of the involvement of each actor in a network. A system is said to be centralized when all the relations involve the same actor [START_REF] Burt | Models of Network Structure[END_REF][START_REF] Burt | Toward a Structural Theory of Action, Network Models of Social Structure, Perception, and Action[END_REF]. This feature greatly contributes to the description of inequality in actors' relations [START_REF] Burt | Models of Network Structure[END_REF]. Although some authors argue the importance of peripheral positions [START_REF] Granovetter | The Strength of Weak Ties[END_REF], centrality in the network is generally supposed to produce power [START_REF] Bonacich | Power and Centrality: A Family of Measures[END_REF]. The difficulty remains how to assess this concept of centrality.

How can one identify the 'most important' actors in a social network? How can we manage to highlight the differences between important and unimportant actors? Many authors agree that the most important or most prominent actors are usually located in strategic locations within the network. In a graphicaI representation of a network, if we consider the term centrality to refer to its center, i.e. its centroid, one can ask whether this center really contains the most important person. An actor is prominent if "the ties of the actor make the actor particularly visible to the other actors in the network" [START_REF] Wasserman | Social Network Analysis: Methods and Applications[END_REF]. The ties concerned here are not only direct ties but also indirect paths involving intermediaries.

Authors such as Knoke and Burt have distinguished two classes of prominence: centrality and prestige [START_REF] Wasserman | Social Network Analysis: Methods and Applications[END_REF]. The most intuitive definition of centrality is to consider that a central actor is the one involved in many ties [START_REF] Bavelas | A Mathematical Model for Group Structure[END_REF][START_REF] Bavelas | Communication Patterns in Task Oriented Groups[END_REF][START_REF] Wasserman | Social Network Analysis: Methods and Applications[END_REF]. Many

experiments and extensions concerning this concept have been proposed [START_REF] Wasserman | Social Network Analysis: Methods and Applications[END_REF]. Several measurements have been proposed in the past to assess an actor's "importance". Differences in indexes are based on the level of analysis. It may be the actor (activity (degree and related measures)

and position (between-ness, closeness)), the dyad (dyadic measures), or the network (eigenvector, flow-between-ness). Another difference depends on the data. The relationships may be symmetric or not. When symmetric, relationships from A to B and B to A are equal. When asymmetric, the information flow from A to B may differ from B to A. When the communication flow is symmetric, related indexes are labeled "centrality", whereas for asymmetric communication flow, related indexes are labeled "influence" (See Wasserman and Faust,199] for a detailed description). Several assessments can be used to measure the centrality concept. They are summarized in Table 2.

Between-ness

Strategic location on paths linking pairs of actors. Position which implies controlling, or increasing the dependence of others.

Closeness

A measure of independence from others. Measure which also represents efficiency.

Flow-between-ness

When between-ness is applied to a whole social network.

Eigenvector A measure of an actor's connections to others, weighted by their centralities.

Dyadic Influence A measure of the relative influence between pairs of actors.

Information

A measure of the quantity of information which is contained in the paths that originate (and end) at an actor.

DATA COLLECTION

We favoured in this study a collecting method based on quantitative observation of the communicational exchanges, from technical sensors in the firms; in this case, the electronic mail servers. By doing so, we made it easier to reproduce the process, and we also avoided some bias and disadvantages [START_REF] Thiétart | Méthodes de Recherche en Management[END_REF][START_REF] Mourgues | Questions de Méthodes en Sciences de Gestion, sous la direction de Nathalie Mourgues[END_REF][START_REF] Mintzberg | The Nature of Managerial Work[END_REF]. The data in this study were not collected by questionnaires; we analyzed data coming from individual actions rather than perceptions.

Independent variables

Several variables were available to describe the organizational context. The aim was to test the relationships between personal and organizational attributes and centrality indexes. Both organizational and individual attributes came from a human resources management system. These data are used to identify employees and to manage resources (wages, promotion, training, and so on).

Information has been selected from these data according to two criteria.

The first criterion is personal. Age, gender, seniority, and diploma were initially selected to better identify personal features. However, due to unreliable information, 'diploma' was removed from the list. Experience and age influence the way people use technologies [START_REF] Limayem | Utilisation des messageries électroniques: mesures objectives versus mesures subjectives[END_REF]. This influence is explicitly mentioned in the Unified Theory of Acceptance and Use of Technology (UTAUT) [START_REF] Venkatesh | User acceptance of information technology: Toward a unified view[END_REF]. These indexes are used to identify the effect of experience on e-mail centrality. Age may be relevant considering that young people are better trained and more aware of internet related technologies [START_REF] Boukef | Les facteurs déterminants du courrier électronique[END_REF]. People that have worked for a long time in the firm are well-known and integrated into the professional social network, which explains why seniority in the firm may influence centrality indexes.

Gender differences in the IS workplace exist (see, for example, [START_REF] Igbaria | The Impact of Job Performance Evaluations on Career Advancement Prospects: an Examination of Gender Differences in the IS Workplace[END_REF]. However, its effect on e-mail use is not always significant [START_REF] Boukef | Les facteurs déterminants du courrier électronique[END_REF]. Gender is selected to measure its effect on centrality.

The other criterion is organizational. Data are selected to better describe organizational power attributes. Based on tacit and explicit relationships among workers, a quantitative measure of an individual's power in an organization is difficult to achieve. However, one can consider that power is not homogeneously distributed within organizations. The aim is to select relevant attributes of organizational power. Four variables have been selected:

 Salary level: the more your work is important and provides added value, the more your salary level should increase. This rationale supposes that the organization is rational and can identify individual performance. If a person's skills and abilities are not properly recognized, he or she will probably look for other jobs with better wages. Conversely, the more people are remunerated, the more their skills and abilities are recognized, but individual remuneration is a cost for the firm. The level of remuneration is the result of negotiation and it depends on an individual's power in the firm. People keep on working in a firm when a balance is realized between individual power and organizational needs. The more the organizational performance is dependent on these skills and abilities, the more people are remunerated.

 Organizational Status: According to [START_REF] Mintzberg | The Manager's Job: Folklore and Fact[END_REF], organizational status is related to formal authority and power. Managers' informational requirements increase as a function of the levels of uncertainty and ambiguity [START_REF] Daft | Organizational Information Requirements, Media Richness and Structural Design[END_REF][START_REF] Baile | Le succès de l'utilisation de la messagerie électronique -étude de ses déterminants au sein d'une unité de production aéronautique[END_REF]. However, results from different studies are not homogeneous. Some of them find a significant relationship between the use of email and the hierarchical level, while some others do not find such a relationship [START_REF] Boukef | Les facteurs déterminants du courrier électronique[END_REF]. In this study, people are associated with an organizational status varying from Chief Executive Officer, Senior Manager, etc. to Employee and Worker. Thus, individuals are ranked according to the internal hierarchy described in the organizational chart. Organizational status ranks people and displays organizational power in the firm.

 Symbolic attributes of organizational power: These symbolic attributes are generally related to scarce resources: a personal car parking space, a company car, high class travel. The attributes used in this study are having a cellular telephone, and having a personal telephone number.

Dependent variables

The dependent variables are the centrality indexes described above. The data used to process these indexes were based on quantitative observation of the electronic mail exchanges in a firm. Every user had an electronic mail box available on the electronic mail server. Every message sent or received by each user was stored in a log file (the server's record). Each week, data from this file were extracted. Weekly extractions were justified because of technical constraints (loading time, volume). A database covering electronic mail exchanges was constituted and completed little by little. This database contained:

the identification number of the message, -the electronic mail address of the receiver, -the electronic mail address of the sender,

the date and time of the exchange,

the volume of the message (the volume of the message (kilobytes) has not been taken into consideration in this work).

Most of the automatic messages, like virus alarms, were identified and removed.

However, automatic but involuntary messages (such as some viruses which send messages to address books) were not detected. However, these messages should not deeply bias the results. Antivirus and firewall systems limit the consequences of this problem, and in any case we did not encounter it during the data collection. The other automatic messages (such as acknowledgements)

were considered as normal messages. The contents of the electronic message were not read. Thus, the employees' privacy rights were respected.

Using the Ucinet software (V6.00), several centrality indexes were computed for these data. All exchanges between the 385 e-mail users were taken into account.

As a result, the analysis treats all kinds of ties within the firm's social network.

This global approach, including low density links, is important because of "the strengths of weak ties" [START_REF] Granovetter | The Strength of Weak Ties[END_REF].

There were 291,869 messages collected over five months. Of these, only internal messages were studied, so that in all, 188,198 messages were processed. From these data, a flow matrix was constructed. This matrix is the raw material for the centrality indexes described above and 36 indexes were treated with Ucinet using the centrality option. However, these indexes were often highly correlated.

A measurement assessment had to be carried out in order to reveal the main factors embedded in the data.

MEASURE AND MODEL ASSESSMENTS

Methodology and Criteria

The measure of centrality is built upon SNA using Ucinet 6 software. A measure assessment process was used to select the relevant indexes and calculate the factors. This was achieved using the correlation coefficient, by removing indexes which were too close together. The Kaiser, Meyer, Olkin (KMO), the Measure of Sampling Adequacy (MSA) and Bartlett's Sphericity Test criteria were used to measure the data adequacy and to select relevant variables. To calculate the factors, the maximum likelihood method was used. Factors were selected according to the Kaiser criterion (eigenvalues greater than 1), and the rotated factor matrix (varimax) method was used to identify initial measures.

LISREL software was used to test the Structural Equation Modeling (SEM) that links individual and organizational characteristics to centrality factors. The model was tested with the Maximum Likelihood method. To evaluate its fit, one can use several criteria. The main fit indexes described in the literature (see [START_REF] Jöreskog | Statistical analysis of sets of congeneric tests[END_REF]Sörbom, 1993, 2001 for detailed information) are summarized in Table 5.

The initial SEM was set up in order to identify and evaluate the relationships between individual and organizational characteristics on the one hand, and the centrality indexes on the other. However, according to the fit indexes, this theoretical SEM model poorly fits the one embedded in the data. It has been changed according to LISREL results (Modification indexes, Chi-square expected change, observation of the covariance/correlation matrix, residuals, etc.) in order to enhance the fit. The results of the final model are described below.

The final model was composed of measurement models and a structural model.

Measure models for the centrality indexes are composed of five factors. Thus, the model is unlikely to be poorly specified and the estimates of the structural parameters can be used for analysis. The equations below describe the final structural model.

Results description

One can see that the centrality factors are fairly well explained with the R2 index which is the percentage of explained variance, ranging between 0.61% and 63%.

It means that the centrality factors are fairly sensitive to the dependent variables.

The eigenvector (F3, R 2 =1.9%) and Hubbel dyadic influence (F5, R 2 =0.61%) are not explained at all. Communication activity (F1, R 2 =29%) and Katz relative influence (F2, R 2 =26%) are more sensitive to the effects of the dependent variables. The information index (F4, R 2 =63%) is the most sensitive. This index measures "how much information is contained in the paths that originate (and end) at a specific actor" [START_REF] Wasserman | Social Network Analysis: Methods and Applications[END_REF]. In other words, one can consider the information index as a control level over the information flow within the network. This control level is not the one described in the organizational chart but the one emerging from collective action, embedded in the human relationships. This control level over information flow is significantly related to Gender (1.20, t=6.72), the use of a professional cellular phone (0.52, t=6.63), the salary position (0.51, t=6.37), and the attribution of a specific professional telephone number (0.18, t=3.66). One can notice that seniority in the firm (-0.039, t=-2.55) inhibits the information index. In other words, in this firm, seniority does not increase control over e-mail information flow. People who have worked for a long time within the firm may not see the use of e-mail, and keep on using traditional media such as the telephone, fax or meetings. Conversely, young people are more aware of and trained in this internet technology, and they probably better understand the advantages of using this asynchronous communication system. Moreover, one can notice that organizational status does not have a significant effect on the control over e-mail information flow. It means that a difference exists between organizational hierarchy, the official structure, and the one embedded in the e-mail communication flow. It lends weight to the hypothesis that the structure of human relationships, studied by SNA, is hardly influenced by the official structure.

Another reading is to consider the dependent variables. One can see that, whatever the centrality factor, the dependent variable effects are homogeneous.

When significant, the coefficients influence the centrality indexes in the same way (positive or negative). With coefficients greater than 1.20, the gender effect is significantly positive for communication activity (F1) and control over information flow (F4) . It is not significant for the other centrality indexes. It means that, when significant, women are more related to a high level of centrality. The use of a professional cellular telephone is positively correlated to F1 and F4. It means that when people have a professional cellular phone they are probably more central in the network. This correlation is less important for the traditional telephone. A direct professional telephone number is positively correlated to centrality for Katz relative influence (F2) and control over information flow (F1). Both of these attributes, the use of a professional cellular telephone and of a traditional one, describe the use of communication tools. One can see that the use of these tools is positively correlated to e-mail centrality indexes. In other words, traditional telephone and cellular phones are not competing with e-mail. The increase of communication needs, such as mobile communication, has generated the use of a new tool, the cellular telephone. Thus, people are continuously linked to the network and the communication flow increases. To deal with this phenomenon, people are using more and more communication tools to process the information flow, such as asynchronous communication tools (e-mail, Short Message Service (SMS), and so on) . [START_REF] Kalika | Le défi du e-management[END_REF] considers that the uses of these tools are complementary, in stratum, in which the use of traditional communication technologies keeps on growing alongside the new ones. These uses are stacked, closely linking the tools and communication contexts (Cucchi A., 2004).

Salary coefficients are significant in the communication activity (F1), Katz relative influence (F2) and control over information flow (F4) . Therefore, it follows that, the higher the salary, the more central the actor. If one assumes that salary is proportional to the individual's value in the organization, salary is not directly linked to the organizational chart. Thus, specific skills, technical knowledge, personal involvement, and so on may enhance wages. According to the 20 equations above, salary is more closely related to the centrality indexes than the organizational status, which is not significantly correlated with any centrality indexes. As a result, status is not a relevant item to explain an actor's centrality of in the e-mail network.

Seniority coefficients are negatively correlated to centrality indexes. Young people are more aware of new technologies, such as e-mail, and can adopt them quickly, whereas older people do not want to disturb their habits; senior staff members probably use more traditional media such as the telephone. The table above summarizes the results. Women are more central. The organizational power "in action", measured by the symbolic attributes of power (telephone number, cellular) and salary level, increases actors' centrality.

"Official" organizational power measured by organizational status has no significant effect on centrality. On the other hand, seniority inhibits actors' centrality. These results lead to some interpretations that are developed in the discussion section below.

DISCUSSION

The results above show significant correlation between the centrality indexes (Information, degree, dyadic measures) on the one hand, and individual and organizational attributes on the other. However, they reveal the difference between the structure described in the organizational chart and the one embedded in the communication flow. E-mail communication activity reveals a structure and results show that it is not correlated to the actors' status. The question is about the nature of this emergent structure.

If one assumes that the level of communication centrality is correlated to the level and the nature of decision activity, central actors process a lot of information in reaching decisions. According to the IP view of the organization, communication flow converges to information-processing requirements. Thus, central actors are the ones for whom information-processing requirements are highest. As centrality indexes are not significantly correlated to status, decision activity is not correlated to organizational status. A high quantity of information is required in contexts of ambiguity and uncertainty. Strategic decisions are typically made in such contexts. Thus, senior managers taking strategic decisions need a huge amount of information for a small number of decisions. Conversely, operational decisions need little information, but the frequency of these decisions is high. Employees and junior managers need a lot of information to make these operational decisions. As a result, communication flow related to decision activity is shared along the organizational chart, whatever the status of the actor.

However, information and decision processes are not always closely linked. [START_REF] Dennis | Information Exchange and Use in Group Decision Making: You Can Lead a Group to Information, but You Can't Make It Think[END_REF] showed that if informational technology (GSS) "enabled groups to exchange more information […], it did not help -perhaps even hinderedparticipants' ability to process it. In short, GSS use can lead participants to more information, but it can't make them think about it". A more realistic assumption is that e-mail communication flow is embedded in the human interactions of the organization. It means that it results from different activities: decision-making roles, communication and coordination activities, social interactions, and so on.

In this case, the structure that emerges from e-mail communication activity, that we can call "communicational structure", depends on multiple factors. It is the result of dynamic exchanges that are at odds with the traditional static view of the organizational chart. Dynamic and grounded in actors' interactions, one can assume that this structure results from a structuring process as described in Giddens' research [START_REF] Giddens | La constitution de la société[END_REF][START_REF] Cucchi | Structuration des communautés cognitives[END_REF]. Although it is not the purpose of this paper, a qualitative and long-term study of e-mail use could help us better understand the role of electronic media in the structuring of three systems: the meaning system with semantic rules, the domination system with resource allocation rules, and the legitimization system with moral rules. In such a study, one could link the centrality indexes to the semantic system (communication activity) and to the domination system (organizational power) .

But message content analysis may provide more explanations of this phenomenon, allowing us to describe recurrent communication processes such as the genres described in Yates and Orlikowsky's research (Yates and Orlikowski, 1992;[START_REF] Orlikowski | Shaping Electronic Communication: The Metastructuring of technology in the context of use[END_REF][START_REF] Ducheneaut | The social impacts of electronic mail in organizations: a case study of electronic power games using communication genres[END_REF]. It should provide fruitful information about the characteristics of this underground communicational structure and about its coexistence with the formal one. As mentioned by [START_REF] Ducheneaut | The social impacts of electronic mail in organizations: a case study of electronic power games using communication genres[END_REF], the relationships between the use of ICT (communicational structure) and the relational power games which take place in organizations (structure of organizational power) are complex. According to his study, large organizations can maintain their older corporate structure after the introduction of ICT. Networked e-mail capabilities can coexist with an established hierarchy. In our study, the organizational status following from the formal authority described in the organizational chart is not significantly correlated to actors' centrality in the communicational structure. It means that, in this firm, the communicational structure is loosely linked to formal authority. As a result, further studies must be carried out to better interpret this phenomenon.

From a methodological point of view, the data used came from the e-mail management system log. Other communication technologies handle logs, such as Private Automatic Branch Exchanges (PABX) which use logs in managing telephone invoicing and in avoiding undesirable behavior, servers, network devices such as firewall, gateways, and so on. These communication devices store informational traces of social relationships. This work shows that one can compute indexes with these data. Graphical representations can be used to improve the understanding of this structure [START_REF] Cucchi | Etude de la communication par l'Analyse des Réseaux Sociaux; application à la messagerie électronique[END_REF] . Many approaches study the organizational structure using questionnaires, senior manager interviews, etc. These methods have provided relevant insights but they cannot consider the structure in action. Informational technologies provide operational data to puzzle out the structure in action. Up until now, these communicational 23 traces have been scattered in specialized devices. With technological convergence, one can expect that the collection of these data will be easier and centralized, using homogeneous formats. Based on these data, indexes and graphical representations will provide relevant reports about the organizational structure and its evolution. SNA indexes, such as centrality indexes, provide relevant metrics to better interpret these data. As a result, the electronic communicational traces will allow managers to lift the veil on the nature and the dynamic of the organizational structure. organizational power measured by the organizational status has no significant effect on centrality. On the other hand, seniority inhibits actors' centrality.

However, certain constraints limit the results described above. The data collected came from a single group. Research in other contexts must be carried out in order to compare the strengths of the relationships and one of the measures used. Moreover, the data came from an email server and a staff file. Email use may cause interference in the social relationships. Technical aspects of email use may filter and transform professional and social relationships. Email, as a communication tool, may have affected the way people interact. Thus, these results are relevant in a mediated social network context. They must be compared to ordinary social network analysis.

From a methodological point of view, it should be noted that the data collection method was original. This research used data from an email server and an organizational staff file. By doing so, perceptual data constraints were avoided.

Perceptual and measurement biases were minimized in as far as questionnaires

were not used to identify email use. Information Systems (IS) tools provide relevant information to observe the communicational structure of the organizational relationships. Individual observations may be used to describe local interactions in a team, with a limited number of actors. IS tools provide information about the overall organization. They allow researchers to go one step further and to reach the organizational and inter-organizational levels. Now, organizational area can be observed directly, simultaneously, as a whole. chantal.fuhrer@univ-reunion.fr

  These measures allow us to better interpret the centralization dimension of the structure embedded in the e-mail communication flow. They are used in an empirical study of the e-mail communication exchanges of a firm.METHOD PARTICIPANTSThe study of electronic mail exchanges took place in a group with 1452 employees. It is composed of 36 firms. This group carries out trade activities related to automobile and goods distribution. Transversal services manage common activities (staff services, accounts department, management). They correspond to the strategic apex and to the techno-structure in the Mintzberg configuration(1982). All 385 employees with an electronic mail address are considered.

F1

  is an activity-based factor. According to the Freeman definition, this factor is viewed as an index of communication activity. F2 and F5 measure the dyadic influence of each actor within the network. F5 is an absolute measure according to the Hubbel definition, whereas the F2 ones are relative according to the Katz definition. F3 is a measure where the centrality is a function of the centrality of the other actors. F4 is an extended measure of between-ness that takes into account all paths from an actor to another weighted by their length. It is an information measure related to the position in the network.These factors are used to describe actors' centrality in the e-mail network. They are used as dependent variables in a structural equations model. In this model, organizational and individual attributes are the independent variables (see the table of independent variables). As the results show, the indexes indicate a very good overall model fit.

CONCLUSION

  This work aimed to test the hypothesis that individual and organizational power attributes affect an individual's centrality within the social network of a firm. To do so, individual and organizational power attributes and centrality concepts have been discussed. Related indicators have been chosen. Using data from 385 employees' mail exchanges in a group, a structural equation model has been derived. The model tests the influence of individual and organizational power attributes on actors' centrality in the e-mail network. The structural equation model converges. Results show that women are more central. The organizational power "in action", measured by the symbolic attributes of power (telephone number, cellular phone) and salary level, are related to actors' centrality. "Official"

  However, this study is quantitative in nature. It focuses solely on the flow of communication without looking at the content. Its purpose is to study the communicational structure and to show that it can reveal information improving our understanding of organizations. It is complementary to the content analysis that may reveal crucial, even contradictory findings. For instance, the content of the messages may show in what proportion the use of these internet technologies provides the actors with new ways to use 'political tactics' and to gain more power. From a managerial point of view, these results show that individual and organizational attributes are correlated to actors' centrality. These results can be interpreted from a human resources' point of view. Centrality measures reflect the level of individual involvement in the network. They may provide useful information for promoting involved employees. Moreover, such an approach should provide insight into managerial decision consequences. Training, teambuilding, pay raises, etc. should influence employees' involvement and interactions. Social network analysis associated with IS tools should help managers to diagnose organizational issues and to evaluate decision consequences. In other words, the e-mail system provides fruitful information to analyze the communicational structure and its evolutions. Alain Cucchi is an associate professor of Management Information Systems in the University of La Réunion (France). Prior to joining University of La Réunion, he has held executive position in information systems department of firms : AXA (insurance), RFO (television), PROTEL (telecommunication). He received his Ph.D from the University of la Réunion. His research interests include technologies adoption, social network analysis, communities, biomimetic approaches, organizational structures, computer-mediated communication and related topics. His research has been published in Systèmes d'Information et Management, La Revue des Sciences de Gestion, Cyber Psychology and Behavior, Fuzzy Economic Review. He is reviewer for Systèmes d'Information et Management, Information Systems Journal and for french national conferences . 7151, 97715 Saint-Denis Messagerie Cedex 9, Reunion. alain.cucchi@univ-reunion.fr Chantal Fuhrer is Associate Professor of Management and Information Systems at the French Business School of Reunion. Her Ph.D. in Management Science was awarded by the University of Reunion. Her research interests include organizational communication, usages contexts analysis of electronic medium in professional areas, media complementarity or substitution, sociometric approach, structuration of exchanges networks. Her articles have appeared in Systèmes d'Information et Management, and papers presented at various national and international conferences, including AIM (Association Information et Prior to joining the academic community, she worked in Information Systems Departements for banks, insurance companies, and administration. She is a member of french Association Information et Management and also

Table 2 :

 2 Summary of centrality assessmentsDegreeA measure of activity. Central actors have the most ties to other actors in the network.

Table 3 :

 3 Independent variables

	Gender	Sex gender (0=male, 1=female)	Igbaria and Baroudi, 1995; Boukef, Kalika, 2002
		Age	Limayem, Bergeron, Richard,
	Seniority	Seniority in the firm	1997; Boukef, Kalika, 2002;
		Seniority in the job	Venkatesh et al., 2003
	Personal telephone number	Does the firm allocate a personal telephone number? (0=no, 1=yes)	Pfeffer, 1981
	Cellular	Does the firm allocate a cellular telephone number? (0=no, 1=yes)
	Salary Position	Salary position within the firm	Mintzberg, 1975; Daft, Lengel, 1986; Boukef, Kalika, 2002;
	Status	From worker (1) to manager (5)	Baile,Lefievre, 2003

Table 4 :

 4 Centrality Factors (dependent variables)

	Centrality Factors	Centrality Indexes
	F1	Degree Fragmentation
	F2	Katz Relative Dyadic Influence Katz Relative Score Influence
	F3	Eigenvector
	F4	Information
	F5	Hubbel Dyadic Influence

Table 5 :

 5 Model Adjustment

	Index	Criterion	Value
	Chi Square (2)	As small as possible	48.79
	2/ df	< 2	1.11 (df=44)
	GFI (Goodness of Fit Index)	 0.9	0.98
	AGFI (Adjusted GFI)	 0.9	0.96
	RMSEA	< 0.05	0.017
	RMR (Root Mean Square Residual)	< 0.05	0.018
	NFI	> 0.9	0.98
	CFI	> 0.9	1.00
	NNFI	> 0.9	1.00

Table 6 :

 6 The Structural Model Equations

	R² = 0.29
	F1= 1.27*Gender + 0.16*Senior -0.34*TelNb + 0.56*Cell + 0.43*Salary -0.016*Status
	(0.46)	(0.13)	(0.48)	(0.31)	(0.094)	(0.028)
	2.73	1.21	-0.70	1.81	4.54	-0.58
	R² = 0.26
	F2=0.0*Gender -0.19*Senior + 0.90*TelNb -0.19*Cell + 0.47*Salary -0.039*Status
		(0.060)	(0.26)	(0.12)	(0.11)	(0.067)
		-3.17	3.47	-1.54	4.31	-0.58
	R² = 0.019
	F3=-0.35*Gender -0.12*Senior + 0.16*TelNb -0.18*Cell + 0.0036*Salary -0.031*Status
	(0.25)	(0.085)	(0.32)	(0.19)	(0.090)	(0.054)
	-1.38	-1.42	0.50	-0.98	0.040	-0.57
	R² = 0.63
	F4=1.20*Gender -0.039*Senior + 0.18*TelNb + 0.52*Cell + 0.51*Salary + 0.086*Status
	(0.18)	(0.015)	(0.050)	(0.078)	(0.080)	(0.059)
	6.72	-2.55	3.66	6.63	6.37	1.46
	R² = 0.0061
	F5=0.0*Gender + 0.0*Senior + 0.0*TelNb -0.052*Cell -0.046*Salary + 0.0*Status
				(0.053)	(0.053)
				-0.99	-0.88

Table 1 :

 1 Effects on centrality

		Gender (1=Women)	Seniority	Telephone	Cellular	Salary Level	Status
	Centrality	+	-	+	+	+


Rafik Absi

Oscillatory and pulsatile flows in environmental, biological and industrial applications

Keywords: Oscillatory flow, pulsating flow, wall shear stress (WSS), waves, arteries, fouling deposits

The understanding of oscillatory and pulsatile flows is of high interest for different environmental/coastal, biological/health and industrial applications. Marine and coastal environment is dominated by waves. The related oscillatory turbulent boundary layers are involved in different coastal engineering applications. In the circulatory system, the study of the pulsatile flow of blood is indispensable for the better comprehension of many cardiovascular diseases. In bio-industries, pulsed flows are used in the cleaning of fouling deposits in different equipment. These different flows require deep understanding of advanced concepts in fluid mechanics and need an adequate quantification of the involved parameters such as wall shear stress (WSS). This study shows interdisciplinary knowledge from different communities: Environment/Coastal engineering, Health/Medicine and Bio-Industries/Chemical engineering. The knowledge acquired within a specialty could be of interest to others. It is important to share and use knowledge beyond disciplines especially in fluid mechanics which is at the crossroads of different applications. This study aims transdisciplinary research strategies toward a holistic approach.

Introduction

Over these last decades, research in fluid mechanics has shown a real enthusiasm for the understanding of periodic (oscillatory and pulsatile) flows. This was motivated by potential applications in the environmental/coastal, biological/health and bio-industrial sectors.

Marine and coastal environment is dominated by waves. This motion produces an oscillatory flow near the bottom [START_REF] Jonsson | Wave boundary layers amd friction factors[END_REF]. The understanding of these flows required many theoretical, experimental and numerical studies [START_REF] Kajiura | A model of the bottom boundary layer in water waves[END_REF]). In addition to wave flume experiments, oscillating water tunnel measurements were of crucial importance to better understand oscillatory turbulent boundary layers [START_REF] Jensen | Turbulent oscillatory boundary layers at high Reynolds numbers[END_REF]. This knowledge is important for the study of coastal sediment transport [START_REF] Fredsoe | Mechanics of coastal sediment transport[END_REF][START_REF] Nielsen | Coastal bottom boundary layers and sediment transport[END_REF][START_REF] Van Rijn | Principles of sediment transport in River, Estuaries and Coastal Seas[END_REF].

The flow of blood is pulsatile in the circulatory system. Its study is indispensable to understand better many cardiovascular diseases [START_REF] Rammos | A computer model for the prediction of left epicardial coronary blood flow in normal, stenotic and bypassed coronary arteries, by single or sequential grafting[END_REF]. Physiological and cardiovascular fluid mechanics provide an understanding of advanced concepts in fluid mechanics * Corresponding author. Email: r.absi@hubebi.com ; rafik.absi@yahoo.fr related to pulsatile flows in elastic tubes as arteries [START_REF] Canic | Blood flow through compliant vessels after endovascular repair: wall deformations induced by the discontinuous wall properties[END_REF][START_REF] Mynard | A numerical model of neonatal pulmonary atresia with intact ventricular septum and RV-dependent coronary flow[END_REF].

Pulsed flows are used in the cleaning of fouling deposits in bio-industrial equipment [START_REF] Gillham | Enhanced cleaning of whey protein soils using pulsed flows[END_REF][START_REF] Blel | Application of turbulent pulsating flows to the bacterial removal during a cleaning in place procedure. Part 1: Experimental analysis of wall shear stress in a cylindrical pipe[END_REF]. Cleaning needs to be more optimized by reducing excess energy and excessive resources (water and chemicals). This optimization needs an adequate quantification of the involved parameters such as forces/energy required for the removal of deposits.

Wall shear stress (WSS) is a parameter of common interest. In coastal engineering, it is involved in the incipient motion of sediments and in turbulence modeling. In medicine, WSS is related to several endothelial dysfunction and cardiovascular disease as atherosclerosis. In industry, deposit removal depends on WSS values.

The principles of conservation of mass, momentum and energy provide the main equations of fluid flow which are non-linear, partial differential equations and need numerical solutions. Computational fluid dynamics (CFD) modelling provides detailed pressure and flow fields and the quantification of the involved parameters. For some cases, it is possible to obtain analytical solutions from simplifications of these equations [START_REF] Absi | Analytical solutions for the modeled kequation[END_REF].

( ) = sin( ) if ∈ 0, /2 0 if ∈ /2, (2)
which is a schematic representation of the systolic and diastolic phases of the cardiac cycle. Another simple pulsed flow (fig. 1,c) given by

( ) = | sin ( )| (3)
has a shape similar to those used in cleaning of industrial equipment. These three flows are identical in the first halfperiod and therefore same methods could be applied there.

In the following sections, we will present first the results related to wave boundary layers, then to pulsatile flows in arteries and finally to pulsed flows for the cleaning of industrial equipment.

Oscillatory bottom boundary layers

The resolution of coastal engineering problems such as transport of sediments needs the understanding of the bottom boundary layer flow. The turbulent wave boundary layer has been the subject of many researchers: [START_REF] Kajiura | A model of the bottom boundary layer in water waves[END_REF], [START_REF] Myrhaug | On a theoretical model of rough turbulent wave boundary layers[END_REF], [START_REF] Sleath | Seabed boundary layers, The Sea[END_REF], [START_REF] Fredsoe | Mechanics of coastal sediment transport[END_REF], [START_REF] Nielsen | Coastal bottom boundary layers and sediment transport[END_REF][START_REF] Van Rijn | Principles of sediment transport in River, Estuaries and Coastal Seas[END_REF], [START_REF] Tanaka | Full-range equation of friction coefficient and phase difference in a wave-current boundary layer[END_REF] and others.

The distribution of eddy viscosity within the oscillatory boundary layer generated by waves is a key parameter in coastal engineering. Adequate description of eddy viscosity distribution in boundary layers is needed for accurate predictions of velocity profiles. Eddy viscosity is also related to sediment diffusivity which is involved in the calculation of sediment concentration profiles and therefore for the prediction of sediment transport by waves. For practical applications in coastal engineering, the eddy viscosity is obtained by RANS turbulence models as twoequation models (k-ε, k-ω, …), or by simple analytical formulations. The well-known are the parabolic-uniform profile [START_REF] Myrhaug | On a theoretical model of rough turbulent wave boundary layers[END_REF][START_REF] Van Rijn | Principles of sediment transport in River, Estuaries and Coastal Seas[END_REF][START_REF] Liu | A two-phase flow model for asymmetric sheet-flow conditions[END_REF] and the exponential-linear profile [START_REF] Hsu | Calibration of Businger-Arya type of eddy viscosity model's parameters[END_REF]Jan 1998, Absi 2010). The exponential-linear profile is an exponential law modulated by a linear function given by

= * ( / ) ( 4
)
where * is the friction velocity, zh is the water depth or the distance from the wall to the axis of symmetry (for oscillatory water tunnel experiments) or free surface, = 0.41, and are coefficients. The validation and calibration of this analytical profile were performed by comparisons with the period-averaged eddy viscosity obtained from the BSL k-ω model [START_REF] Menter | Two-equation eddy-viscosity turbulence models for engineering applications[END_REF][START_REF] Suntoyo | Effect of bed roughness on turbulent boundary layer and net sediment transport under asymmetric waves[END_REF] for different wave conditions through the parameter / where is the wave orbital amplitude and is the equivalent roughness [START_REF] Absi | Eddy viscosity profiles for wave boundary layers: validation and calibration by a k-ω model[END_REF]. 2) presents temporal and spatial variation of dimensionless eddy viscosity for a sinusoidal wave given by Eq. (1). Figure (3) shows comparison between periodaveraged eddy viscosity obtained from the BSL k-ω model (symbols) and Eq. (4) (dashed line). Even if the eddy viscosity is highly time-dependent (fig. 2), the periodaveraged dimensionless eddy viscosity has a shape which is well described by Eq. ( 4) for z/zh < 0.6 (fig. 3). Figure ( 4) shows the comparison for an asymmetric wave given by

( ) = sin( ) -cos(2 ) (5)
Even for the case of asymmetric wave, the period-averaged dimensionless eddy viscosity has a shape which is well described by Eq. ( 4) for z/zh < 0.5 (fig. 4). Figures ( 3) and ( 4) show that the period-averaged eddy viscosity profiles for sinusoidal and asymmetric waves are different. This indicates that the period-averaged eddy viscosity profile should depend on the wave non-linearity parameter given by Ni=(u1+u2)/(2u1) or Ni=uc/û, where uc is the velocity at wave crest and û is the total velocity amplitude. Equation (4) needs the friction velocity which is related to wall shear stress (WSS). In coastal engineering, WSS could be obtained by simple methods as wave friction factor = / [START_REF] Jonsson | Wave boundary layers amd friction factors[END_REF] or the momentum integral method [START_REF] Fredsoe | Mechanics of coastal sediment transport[END_REF].

In the case of uniform flow, the momentum equation is

= -+ (6)
Outside the boundary layer, the velocity is given by the free stream velocity and the shear stress becomes = 0. A simple integral approach is applied to solve the momentum equation =

( ) = - (7)
Where is the wall shear stress (WSS) and is the zero level of the velocity. To solve this boundary layer momentum equation, the shape of the velocity profile is assumed to be logarithmic. This method requires to solve numerically an ordinary differential equation (ODE) [START_REF] Fredsoe | Mechanics of coastal sediment transport[END_REF]. Figure ( 5) shows WSS obtained from Eq. ( 7) over a half-period for a sinusoidal wave for different values of / .

Figure 5. WSS for a sinusoidal wave.

Pulsatile flows in arteries

Physiological and cardiovascular fluid mechanics provided an understanding of advanced concepts in fluid mechanics. The study of blood flow in the cardiovascular system is more complicate since blood is a non-Newtonian fluid and arteries are elastic/compliant tubes.

Blood is a two-phase suspension of suspended elements (i.e., red blood cells, white blood cells, platelets) in an aqueous solution. Blood behaves as a non-Newtonian fluid (i.e., the apparent viscosity of blood depends on the shear forces). The most common non-Newtonian models used for the blood are the power law, Casson, and Carreau-Yasuda models [START_REF] Shibeshi | The rheology of blood flow in a branched arterial system[END_REF]. However, in some cases it is assumed as Newtonian. The description of the flow behavior in arterial vessels (elastic tubes) needs three independent variables namely the pressure ( , ), the fluid velocity ( , ) (or equivalently the flow rate ( , )) and the cross-sectional area ( , ). The main governing equations are the conservation of mass, momentum (i.e. continuity and momentum equations) and energy conservation which is related to the interaction between the fluid and the tube wall [START_REF] Morris | Computational fluid dynamics modelling in cardiovascular medicine[END_REF].

Adequate methods are needed for the quantification of parameters which cannot be obtained experimentally as WSS. WSS is related to several endothelial dysfunction and cardiovascular disease as atherosclerosis [START_REF] Moore | Fluid wall shear stress measurements in a model of the human abdominal aorta: oscillatory behavior and relationship to atherosclerosis[END_REF]. In elastic tubes, fluid-structure interaction has a considerable effect on the WSS calculations. Computational fluid structure interaction (FSI) simulations allow to quantify time-and space-evolution of wall shear stress (WSS). The oscillatory shear index (OSI) is used to describe the unsteady nature of blood flow in arteries, it is defined as

OSI = 1 - | | (8)
OSI varies between 0 and 0.5. It considers the oscillations in the flow direction: the larger the index, the more important / if ≠ 0. where = ℎ / , is the Young's modulus, and, the Poisson's ratio, h0 are respectively the internal radius and the thickness at =0. The arterial capacitance per unit length or cross-sectional compliance may be calculated assuming that vessel length does not vary with transmural pressure.

= (11)

Blood Flow (ml/ s ) Pressure (mmHg)

Pulsed flows for cleaning of industrial equipment

The formation of fouling deposits in process plants of food, cosmetic and pharmaceutical industries is of crucial importance since it can affect microbial sterility and alter the purity of the product. In practice, cleaning is expensive, not only through the cost of the cleaning process by itself, but also by the cost of lost production and the environmental costs related to waste treatment. The actual situation is such cleaning in place (CIP) protocols need to be more optimal particularly by reducing excess energy. The optimization needs an adequate quantification of the required forces/energy required for deposits removal. However, these forces are affected by the interaction between deposits and surfaces. The main questions about the process of deposit removal are as follows: How cleaning is affected by process variables? How to initiate fracture in deposits?

Cleaning is a complex phenomenon. Research conducted during the last decades allowed to highlight the effect of hydrodynamic of the cleaning fluid on CIP efficiency [START_REF] Grasshoff | Hygienic design: The basis for computer controlled automation[END_REF]. Particularly the importance of the flow parameters such as fluid velocity [START_REF] Schlussler | Zur Kinetik von Reinigungsvorg angen an festen Oberflachen[END_REF], shear forces at fluid/equipment interfaces or WSS [START_REF] Sharma | Factors controlling the hydrodynamic detachment of particles from surfaces[END_REF]. The mean WSS was related to the removal of clay deposits and bio-film [START_REF] Bergman | An approach to study and model the hydrodynamic cleaning effect[END_REF]Tragardh, 1990, Hall 1998). In industrial CIP procedures, the used flow for cleaning is in general in turbulent regime [START_REF] Bénézech | Le Nettoyage en Place (NEP)[END_REF].

It is possible to generated flow pulses by bellows units or piston devices allowing low frequencies (<= 2 Hz) [START_REF] Gillham | Enhanced cleaning of whey protein soils using pulsed flows[END_REF] or pulsation generator systems which allows pulsations of high amplitudes and maximum frequency up to 2.86 Hz [START_REF] Blel | Application of turbulent pulsating flows to the bacterial removal during a cleaning in place procedure. Part 1: Experimental analysis of wall shear stress in a cylindrical pipe[END_REF]. Pulsations conditions were defined by opening-closing times and minimum-maximum flow rate. Instantaneous variations of the velocity is represented by a free stream velocity given by ( ) = + sin( 2) = (1 + sin( 2)) ( 14)

where is the frequency of the pulsations (Hz), the steady component, the pulsatile component and = / the dimensionless amplitude of the pulsations.

The experiments of [START_REF] Lelièvre | Cleaning in place: effect of local wall shear stress variation on bacterial removal from stainless steel equipment[END_REF] showed that cleaning depends on both mean WSS and fluctuation rate. Low WSS zones with a high level of turbulence (high fluctuation rate) was shown as very cleanable. Local WSS values were obtained experimentally by using an electrochemical technique. First, the instantaneous value of the wall shear rate ( ) (at the surface of the electrode) is calculated from the instantaneous limiting current, ( ) which is related to the Sherwood number [START_REF] Reiss | An experimental study of the unsteady nature of the viscous sublayer[END_REF][START_REF] Sobolik | Simultaneous measurement of film thickness and wall shear stress in wavy flow of non-Newtonian liquids[END_REF]. The instantaneous value of the wall shear rate ( ) is written as the sum of mean and fluctuating values as

( ) = ̅ + ( ) with ( ) = 0 (12)
The fluctuations were quantified by the fluctuating rate defined by

= ̅ (13)
The mean WSS is obtained by multiplying the mean wall shear rate ̅ by the fluid viscosity. We investigate the efficiency of WSS generated by pulsed flows in removal of tomato deposits (Liu et al., 2006), Figure ( 9) shows pulling energy/force corresponding to a range of different heights above a surface, from 20 to 1500 for baked and unbaked tomato deposits obtained by Liu et al. (2006). For the unbaked data, the energy per unit surface ( / ) required to scrape the deposit is about 1 J/m² and 2 J/m² (Fig. 9.a). The baked data show that the pulling energy increases with height from the surface, up to 16 J/m² then it decreases with distance from the surface until 6 J/m² (Fig. 9.a). From the relation between WSS and head loss, it is possible to write a relation between the energy per unit surface ( / ) in J/m² and the WSS as

= (15)
Where and are respectively the length and surface of a pipe. For a pipe length of 1 meter, the WSS is therefore equal to the pulling energy (energy per unit surface). Eq. ( 15) is used to obtain experimental values of WSS from measured data of pulling energy (fig. 9.a). For the unbaked data, the required WSS to scrape the deposit is about 1-2 Pa and for the baked data it is between 6 and 16 Pa. Figure (9.b) shows that the behavior of the time-dependent force (for 600

) is similar to the shape of the WSS of the first half-period (Fig. 5). The shape of the time-dependent force (Fig. 9.b, amplitude, initial and final times about 7 and 23 , …), could provide indications about the parameters of the used pulsed flow.

For a given pulsed flow, it is possible to calculate mean WSS values from computational fluid dynamics (CFD) simulations based on the Reynolds-averaged Navier-Stokes (RANS) equations or by simple tools as the momentum integral method. In the present simulations, we use Eq. ( 7) to calculate WSS. To be efficient for the removal of tomato deposits, the flow WSS should be at least equal to the required values of WSS obtained from Eq. ( 15 (12) shows that for the same velocity of 0.5m/s the maximum WSS is about 1.8 Pa and therefore could be able to remove the unbaked tomato deposits. The main question is about the use of mean or maximum WSS. Literature review showed that most studies use the mean WSS. However, for these pulsed flows, the pick WSS plays a particular role. More investigations are needed to know how it will be considered in cleaning of industrial equipment.

Conclusions

The research in fluid mechanics related to periodic (oscillatory and pulsatile) flows is of high interest due to the potential applications in the environmental/coastal, biological/health/Medical and bio-industrial/chemical sectors. Marine and coastal environment is dominated by waves/oscillatory flows. In the circulatory system, the blood flow is pulsatile. In bio-industries, pulsed flows are used in cleaning of fouling deposits. Wall shear stress (WSS) is a parameter of common interest. In coastal engineering, it is involved in incipient motion of sediments and turbulence modeling. In medicine, WSS is related to several endothelial dysfunction and cardiovascular disease as atherosclerosis. In industry, deposit removal depends on WSS values.

In coastal engineering both RANS turbulence models and analytical formulations are used. Analytical models need WSS which can be obtained simply by the momentum integral method. In cardiovascular systems, calculations of WSS is more complicated since blood behaves as a non-Newtonian fluid and arteries are compliant tubes. In elastic tubes, fluid-structure interaction has a considerable effect on the WSS calculations. Oscillatory shear index (OSI) is used to quantify the effect of the vessel wall compliance. The Windkessel model, which is based on an electrical analogy, provides accurate time-dependent pressure during the systolic and diastolic phases. The 4-Element Windkessel Model considers the resistance of the arterial system and the aortic valve by two resistors. The arterial compliance is taken into account by a capacitor and the inertia to blood flow by an inductor. In CIP, the fluctuating rate needs to be considered. We investigated the efficiency of WSS generated by pulsed flows in the removal of tomato deposits. Large values of velocities require excess energy. WSS was calculated by the momentum integral method. Results show that for the optimization study, it is more interesting to use a flow with a low velocity and find the adequate period/frequency value. It could be interesting to investigate the effect of flow reversal associated to an oscillatory flow which could be more efficient.

Our study shows that these different flows require deep understanding of advanced concepts in fluid mechanics to allow an adequate quantification of the involved parameters. It is important to share and use knowledge beyond disciplines especially in fluid mechanics which is at the crossroads of different applications. This study aims transdisciplinary research strategies toward a holistic approach.

Figure 1 .

 1 Figure 1. Pure oscillatory flow (a) and simple pulsating flows (b) and (c).

Figure ( 1

 1 Figure (1) shows simple pulsed flows based on a pure oscillatory flow (fig. 1, a) given by the free stream velocity of the wave bottom boundary layer ( ) = sin ( ) (1) Where = 2 / , is the period. A simple pulsatile flow (fig. 1, b) given by

Figure 2 .

 2 Figure 2. Temporal and Spatial Variation of dimensionless eddy viscosity for a sinusoidal wave obtained by the BSL k-ω model, Flow conditions: U0=3,63 m/s ; am=1,73 m ; T=3 s ; ks=1,5 cm, Re=437000.

Figure 3 .

 3 Figure 3. Period-averaged dimensionless eddy viscosity for a sinusoidal wave.

Figure (

  Figure (2) presents temporal and spatial variation of dimensionless eddy viscosity for a sinusoidal wave given by Eq. (1).Figure (3) shows comparison between periodaveraged eddy viscosity obtained from the BSL k-ω model (symbols) and Eq. (4) (dashed line). Even if the eddy viscosity is highly time-dependent (fig.2), the periodaveraged dimensionless eddy viscosity has a shape which is well described by Eq. (4) for z/zh < 0.6 (fig.3). Figure (4) shows the comparison for an asymmetric wave given by

Figure 4 .

 4 Figure 4. Period-averaged dimensionless eddy viscosity for asymmetric wave Ni=0.67.

Figure 6 .

 6 Figure 6. Blood flow in arteries. electric analogy of Windkessel models. (a) 2-Element model, (b) 4-Element model with fluid inertia represented by the inductor LThe Windkessel model is validated by experimental data. Blood flow information was acquired using a cardiac-gated, 2D, respiratory compensated, phase-contrast (PC) cine sequence with through-plane velocity encoding[START_REF] Karmonik | CFD Challenge: Predicting Patient-Specific Hemodynamics at Rest and Stress through an Aortic Coarctation[END_REF]. The cardiac output of the patient was 3.71 L/min, the heart rate 47 beats per minute (cardiac cycle T = 1.277 sec). Figure(7) shows measured and reconstructed time-dependent flow rate at the level of the ascending aorta. A 15-term Fourier reconstruction of the flow waveforms is given by[START_REF] Karmonik | CFD Challenge: Predicting Patient-Specific Hemodynamics at Rest and Stress through an Aortic Coarctation[END_REF]

Figure ( 8

 8 Figure (8) shows time-dependent pressure during the systolic and diastolic phases obtained from the Windkessel model. The dashed line represents the result of the 2-Element Windkessel Model while the solid line is the result of the 4-Element Windkessel Model which allows an accurate

Figure 7 .

 7 Figure 7. Pulsatile blood flow. Ascending aortic flow waveforms (in ml/sec) measured by the (PC)-MRI sequence (Karmonik et al., 2014).

Figure 8 .

 8 Figure 8. Pressure. Dashed-line: 2-Element model; Green solid line: 4-Element model (with inertia: inductance L) It is possible to describe the deformation of the vessel walls (variation in the cross-sectional area or diameter) due to a variation in the transmural (internal minus external) pressure , by a pressure-areaconstitutive relation given by (Absi 2018) = 1 -(10) Where = 1 if = 0 and = (1/(1 -))/ if ≠ 0. where = ℎ / , is the Young's modulus, and, the Poisson's ratio, h0 are respectively the internal radius and the thickness at =0. The arterial capacitance per unit length or cross-sectional compliance may be calculated assuming that vessel length does not vary with transmural pressure.

Figure 9 .

 9 Figure 9. (a) Pulling energy required to disrupt baked and unbaked tomato deposits, as a function of probe cut height above the surface, (b) force-time behavior of baked tomato deposits as a function of probe height above the surface(Liu et al., 2006).

  ) and fig (9.a).

Figure 10 .

 10 Figure 10. Mean WSS for different free stream velocity values for a period T=2s Figure (10) presents mean WSS for different free stream velocity values. It shows that velocities about 0.5 and 1 / allow removal of unbaked tomato ( ≈ 2Pa, fig. 9.a) while larger values up to 3 / are needed for the cleaning of baked one ( ≈ 16Pa, fig. 9.a).However, large values of velocities require excess energy. An optimization study requires the use of low velocities and an adequate period/frequency which will allow removal of deposits with low energy. We use the lowest value of velocity namely 0.5 / to investigate the effect of period/frequency on deposit removal. WSS values (Fig.11) show that a high frequency >3Hz is needed to clean the unbaked tomato. These frequencies seem hardly obtainable by pulsation generator systems (maximum frequency up to 2.86 Hz,[START_REF] Blel | Application of turbulent pulsating flows to the bacterial removal during a cleaning in place procedure. Part 1: Experimental analysis of wall shear stress in a cylindrical pipe[END_REF] and therefore it seems not possible to clean baked tomato at this velocity and frequencies. The optimization study needs more simulations in order to find the more optimal velocity/frequency values allowing cleaning at low costs.

Figure

  Figure (12) shows that for the same velocity of 0.5m/s the maximum WSS is about 1.8 Pa and therefore could be able to remove the unbaked tomato deposits. The main question is about the use of mean or maximum WSS. Literature review showed that most studies use the mean WSS. However, for these pulsed flows, the pick WSS plays a particular role. More investigations are needed to know how it will be considered in cleaning of industrial equipment.

Figure 11 .

 11 Figure 11. Mean WSS for a free stream velocity of = . / . (a) for different periods, (b) for different frequencies

Acknowledgments

The first part of this work was undertaken during the visit of the author at Tohoku University. The author is grateful for the financial support provided by Japan Society for the Promotion of Science (JSPS), within the FY2010 JSPS Invitation Fellowship Program for Research in Japan (No. S-10168).


. Here, we describe DOMO, a new database containing 8877 multiple sequence alignments, including 99 058 protein domains as well as repeating-sequence regions extracted from 83 054 non-redundant amino acid sequences from the SWISS-PROT 7 and PIR 8 databases. The domain boundaries and alignments were generated by a fully automated analysis process that involves the detection and clustering of amino acid sequence similarities and, subsequently, delineation of the domain boundaries and multiple sequence alignment of related protein segments 9,10 . The domain boundaries were not inferred from three-dimensional data. Instead, the relative positions of homologous segment pairs within the same protein (for repeats) or within homologous proteins with regard to each protein's N-or C-terminus were used to define the domain boundaries. The completeness and accuracy of the protein classifications, the correctness of the domain boundaries, and the quality of the multiple sequence alignments are greatly improved in DOMO, in comparison to other databases 9,10 .

The database format

Each entry in the database corresponds to one family of homologous domains. Fields provide information about related proteins, functions of members of each family, decomposition of each protein into constituent domains, multiple sequence alignment, conserved residues and phylogenetic tree. The multiple alignment shown in Fig. 1 includes 16 apple domains from four homologous serine proteases (four apple domains are present in each protein). It should be noted that the aligned fragments were delineated automatically and spliced from the complete sequences before multiple alignment.

Accessing DOMO through the World Wide Web

DOMO can be accessed through the sequence retrieval system SRS 11 at http://www.infobiogen.fr/services/domo/ which provides a form-based query manager allowing retrieval of famillial domain alignments by identifiers, sequence accession numbers, or keywords. Furthermore, the query results can be linked to other sequence databases to collect additional information on the relevant proteins. Domain families can also be translated to the standard MSF or FASTA formats so that they can be processed by other sequence-analysis tools. If the three-dimensional structure of a domain is known, DOMO provides direct links to the corresponding atomic coordinates, RASMOL display 12 , and complementary structural databases. If the domain structure is not known, the entry points to a composite prediction obtained by different techniques such as PREDATOR 13 , SIMPA96 14 , DSC 15 , MAP123D 16 , COILS 17 , or TMAP 18 . Moreover, a fast search for homologous domains can be performed using BLAST2 19 , as can multiple sequence alignment using Clustal W 20 . The SRS steps in such an analysis are described below.

(1) From the SRS 'Select Libraries' page, select SWISSPROT or any other protein sequence database (but not DOMO).

(2) From the 'Query Form' page, formulate a sequence query.

(3) From the 'Query Result' page, launch BLAST2. (4) From the 'BLAST2 options' page, select DOMO as the searched databank (and edit the sequence in query box if desired).

(5) From the 'BLAST2 Query Result' page, push the 'selected' button, select some hits, and launch Clustal W. (6) From the 'Clustal W options' page, push the 'Align the selected hits with the query' button if desired. (7) If the protein has multiple domains, return to 'BLAST2 Query Result' page, and reiterate steps ( 5) and ( 6) with hits from not already aligned DOMO families.

Concluding remarks

The DOMO sequence-analysis environment (domain database, query manager, homology search and multiple-sequence-alignment tools) provides a simple tool for determining domain arrangements, evolutionary relationships, and key amino acid residues in a query protein sequence.

Figure 1

Example of a DOMO database entry : the apple domain. The consensus sequence generated shows residues as lowercase characters if the conservation level is above 85% and below 100%, and as uppercase characters if the position is absolutely conserved. Physico-chemical properties are also shown (e.g. positions that are mainly hydrophobic or hydrophilic residues are indicated by the signs = and #, respectively).

]-------------------------------------------------------------------------390 al P26262 4 385 TKINAR]-------------------------------------------------------------------------390 al P03952 4 385 TKTSTRI]------------------------------------------------------------------------391 al P03951 4 382 TKIKPRI]------------------------------------------------------------------------388 al P03952 2 203 MNIFQHLAFS DVD]------------------------------------------------------------------215 al P14272 2 203 MDIFQHFAFA DLN]------------------------------------------------------------------215 al P26262 2 203 MDIFQHSAFA DLN]------------------------------------------------------------------215 al P03951 2 202 RDIFPNTVFA DSN]------------------------------------------------------------------214 al P03951 1 112 KDIYVDLDMK GIN]------------------------------------------------------------------124 al P26262
1 113 RDIYKGLDMR GSN]------------------------------------------------------------------125 al P14272

1 113 QDIYEGLDMR GSN]------------------------------------------------------------------125 al P03952

1 113 RDIYKGVDMR GVN]------------------------------------------------------------------125 al P03951

3 293 SSFYHDTDFL GEE]------------------------------------------------------------------305 al P03952

3 294 SKIYPGVDFG GEE]------------------------------------------------------------------306 al P26262

3 294 SKIYSGVDFE GEE]------------------------------------------------------------------306 al P14272

3 294 FKIYSGVAFE GEE]------------------------------------------------------------------306 co 81 ##i@##=.f. #.# 93