Innovation through withdrawal. Contribution to a sociology of detachment

To develop the understanding of innovation processes conceptualized in terms of asso- ciation through the "sociology of translation" (cf. actor-network theory) studies, this article analyses innovation processes in terms of dissociation and detachment mechanisms, exami- ning innovation through "withdrawal;" that is, innovation based on reducing or withdrawing use of a practice-"subtracting," "detaching"-a given artefact. Specifically, it focuses on the shift to farming techniques that have eliminated ploughing, bringing to light four major mechanisms constitutive of dissociation: centrifugal association; making entities and asso- ciations visible; making other entities and associations invisible; bringing together or "asso- ciating" new entities. The study helps refine our understanding of the detachment processes at work in innovation, shedding light in this particular case on transfers between public research institutes, industrial companies, farmers and citizens seeking to develop new farm production models.

A inovação por sustração : contribução para a sociología do distanciamento

To develop the understanding of innovation processes conceptualized in terms of association through the "sociology of translation" (cf. actor-network theory) studies, this article analyses innovation processes in terms of dissociation and detachment mechanisms, examining innovation through "withdrawal"; that is, innovation based on reducing or withdrawing use of a practice - "subtracting", "detaching" - a given artefact. Specifically, it focuses on the shift to farming techniques that have eliminated ploughing, bringing to light four major mechanisms constitutive of dissociation : centrifugal association ; making entities and associations visible ; making other entities and associations invisible; bringing together or " associating " new entities. The study helps refine our understanding of the detachment processes at work in innovation.

The local configuration of a science and innovation policy : a city into the nanoworld

Local trajectories and arrangements play a significant role because the development of a research field, such as nanoscience and nanotechnology, requires substantial investments in human and instrumental resources. But why are there often concentrated in a limited number of places? What dynamics lead to such concentration? The hypothesis is that there is an assemblage of heterogeneous resources through the action of local actors. The chapter will explore, from an Actor Network Theory (ANT) perspective, how the local emergence of research dynamics from: the revival of local traditions, the local and national action of institutional entrepreneurs, controversial dynamics, and researchers' arrangements to involve other actors. It will examine how they connect up with each other and mutually commit themselves to the development of new technologies. It will focus on the role of narratives in this assembling: how were the local narratives of the past mobilized and to what effect.

Firm's network capability and innovation performance: evidences from China hi-tech industry

ABSTRACT : A firm's competitive advantage can arise from internal resources as well as from an interfirm network. -This dissertation investigates the competitive advantage of a firm involved in an innovation network by integrating strategic management theory and social network theory. It develops theory and provides empirical evidence that illustrates how a networked firm enables the network value and appropriates this value in an optimal way according to its strategic purpose. The four inter-related essays in this dissertation provide a framework that sheds light on the extraction of value from an innovation network by managing and designing the network in a proactive manner. The first essay reviews research in social network theory and knowledge transfer management, and identifies the crucial factors of innovation network configuration for a firm's learning performance or innovation output. The findings suggest that network structure, network relationship, and network position all impact on a firm's performance. Although the previous literature indicates that there are disagreements about the impact of dense or spare structure, as well as strong or weak ties, case evidence from Chinese software companies reveals that dense and strong connections with partners are positively associated with firms' performance. The second essay is a theoretical essay that illustrates the limitations of social network theory for explaining the source of network value and offers a new theoretical model that applies resource-based view to network environments. It suggests that network configurations, such as network structure, network relationship and network position, can be considered important network resources. In addition, this essay introduces the concept of network capability, and suggests that four types of network capabilities play an important role in unlocking the potential value of network resources and determining the distribution of network rents between partners. This essay also highlights the contingent effects of network capability on a firm's innovation output, and explains how the different impacts of network capability depend on a firm's strategic choices. This new theoretical model has been pre-tested with a case study of China software industry, which enhances the internal validity of this theory. The third essay addresses the questions of what impact network capability has on firm innovation performance and what are the antecedent factors of network capability. This essay employs a structural equation modelling methodology that uses a sample of 211 Chinese Hi-tech firms. It develops a measurement of network capability and reveals that networked firms deal with cooperation between, and coordination with partners on different levels according to their levels of network capability. The empirical results also suggests that IT maturity, the openness of culture, management system involved, and experience with network activities are antecedents of network capabilities. Furthermore, the two-group analysis of the role of international partner(s) shows that when there is a culture and norm gap between foreign partners, a firm must mobilize more resources and effort to improve its performance with respect to its innovation network. The fourth essay addresses the way in which network capabilities influence firm innovation performance. By using hierarchical multiple regression with data from Chinese Hi-tech firms, the findings suggest that there is a significant partial mediating effect of knowledge transfer on the relationships between network capabilities and innovation performance. The findings also reveal that the impacts of network capabilities divert with the environment and strategic decision the firm has made: exploration or exploitation. Network constructing capability provides a greater positive impact on and yields more contributions to innovation performance than does network operating capability in an exploration network. Network operating capability is more important than network constructing capability for innovative firms in an exploitation network. Therefore, these findings highlight that the firm can shape the innovation network proactively for better benefits, but when it does so, it should adjust its focus and change its efforts in accordance with its innovation purposes or strategic orientation.

Mycorrhizal ecology and evolution: the past, the present, and the future.

1406 I. 1407 II. 1408 III. 1410 IV. 1411 V. 1413 VI. 1416 VII. 1418 1418 References 1419 SUMMARY: Almost all land plants form symbiotic associations with mycorrhizal fungi. These below-ground fungi play a key role in terrestrial ecosystems as they regulate nutrient and carbon cycles, and influence soil structure and ecosystem multifunctionality. Up to 80% of plant N and P is provided by mycorrhizal fungi and many plant species depend on these symbionts for growth and survival. Estimates suggest that there are c. 50 000 fungal species that form mycorrhizal associations with c. 250 000 plant species. The development of high-throughput molecular tools has helped us to better understand the biology, evolution, and biodiversity of mycorrhizal associations. Nuclear genome assemblies and gene annotations of 33 mycorrhizal fungal species are now available providing fascinating opportunities to deepen our understanding of the mycorrhizal lifestyle, the metabolic capabilities of these plant symbionts, the molecular dialogue between symbionts, and evolutionary adaptations across a range of mycorrhizal associations. Large-scale molecular surveys have provided novel insights into the diversity, spatial and temporal dynamics of mycorrhizal fungal communities. At the ecological level, network theory makes it possible to analyze interactions between plant-fungal partners as complex underground multi-species networks. Our analysis suggests that nestedness, modularity and specificity of mycorrhizal networks vary and depend on mycorrhizal type. Mechanistic models explaining partner choice, resource exchange, and coevolution in mycorrhizal associations have been developed and are being tested. This review ends with major frontiers for further research.

Structural connectomics in brain diseases.

Imaging the connectome in vivo has become feasible through the integration of several rapidly developing fields of science and engineering, namely magnetic resonance imaging and in particular diffusion MRI on one side, image processing and network theory on the other side. This framework brings in vivo brain imaging closer to the real topology of the brain, contributing to narrow the existing gap between our understanding of brain structural organization on one side and of human behavior and cognition on the other side. Given the seminal technical progresses achieved in the last few years, it may be ready to tackle even greater challenges, namely exploring disease mechanisms. In this review we analyze the current situation from the technical and biological perspectives. First, we critically review the technical solutions proposed in the literature to perform clinical studies. We analyze for each step (i.e. MRI acquisition, network building and network statistical analysis) the advantages and potential limitations. In the second part we review the current literature available on a selected subset of diseases, namely, dementia, schizophrenia, multiple sclerosis and others, and try to extract for each disease the common findings and main differences between reports.

EEG-based functional brain networks: does the network size matter?

Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks--whose nodes can vary from tens to hundreds--are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size. To this end, EEGs from 32 normal subjects were recorded and functional networks of three different sizes were extracted. A state-space based method was used to calculate cross-correlation matrices between different brain regions. These correlation matrices were used to construct binary adjacency connectomes, which were assessed with regards to a number of graph metrics such as clustering coefficient, modularity, efficiency, economic efficiency, and assortativity. We showed that the estimates of these metrics significantly differ depending on the network size. Larger networks had higher efficiency, higher assortativity and lower modularity compared to those with smaller size and the same density. These findings indicate that the network size should be considered in any comparison of networks across studies.

Observing workplace incivility towards women: The roles of target reactions, actor motives, and actor-target relationships

The current study conceptualized observer reactions to uncivil behavior towards women as an ethical behavior and examined three factors (target reaction, actor motive, and actor-target relationship) that influence these reactions. Two vignette studies with women and men undergraduate and graduate students in western Switzerland were conducted. Study 1 (N=148) was a written vignette study that assessed how the reaction of female targets to incivility and the motives of actors influenced observer reactions. Results showed that a female target's reaction influenced observers' evaluations of the harm caused by an uncivil incident, and that an actor's motive affected observers' assessments of the necessity to intervene. Study 2 (N=81) was a video vignette study that assessed the effects of the reactions by female targets to incivility and the relationship between the target and the actor on observer reactions.We found that female targets' reactions influenced observers' evaluations of harm and the perceived necessity to intervene. Furthermore, the effect of a female target's reaction on observers' evaluations of harm was moderated by the relationship between the actor and the target: a female target who laughed at the uncivil behavior was perceived as less harmed, when she and the actor had a personal relationship than when they had a professional relationship. When the female target reacted hurt or neutrally, actor-target relationship did not affect observers' evaluations of harm. We conclude by discussing the implications of our findings for theory and practice.

Quantifying network properties in multi-electrode recordings: spatiotemporal characterization and inter-trial variation of evoked gamma oscillations in mouse somatosensory cortex in vitro.

Linking the structural connectivity of brain circuits to their cooperative dynamics and emergent functions is a central aim of neuroscience research. Graph theory has recently been applied to study the structure-function relationship of networks, where dynamical similarity of different nodes has been turned into a "static" functional connection. However, the capability of the brain to adapt, learn and process external stimuli requires a constant dynamical functional rewiring between circuitries and cell assemblies. Hence, we must capture the changes of network functional connectivity over time. Multi-electrode array data present a unique challenge within this framework. We study the dynamics of gamma oscillations in acute slices of the somatosensory cortex from juvenile mice recorded by planar multi-electrode arrays. Bursts of gamma oscillatory activity lasting a few hundred milliseconds could be initiated only by brief trains of electrical stimulations applied at the deepest cortical layers and simultaneously delivered at multiple locations. Local field potentials were used to study the spatio-temporal properties and the instantaneous synchronization profile of the gamma oscillatory activity, combined with current source density (CSD) analysis. Pair-wise differences in the oscillation phase were used to determine the presence of instantaneous synchronization between the different sites of the circuitry during the oscillatory period. Despite variation in the duration of the oscillatory response over successive trials, they showed a constant average power, suggesting that the rate of expenditure of energy during the gamma bursts is consistent across repeated stimulations. Within each gamma burst, the functional connectivity map reflected the columnar organization of the neocortex. Over successive trials, an apparently random rearrangement of the functional connectivity was observed, with a more stable columnar than horizontal organization. This work reveals new features of evoked gamma oscillations in developing cortex.

Inference about the number of contributors to a DNA mixture: Comparative analyses of a Bayesian network approach and the maximum allele count method.

In the forensic examination of DNA mixtures, the question of how to set the total number of contributors (N) presents a topic of ongoing interest. Part of the discussion gravitates around issues of bias, in particular when assessments of the number of contributors are not made prior to considering the genotypic configuration of potential donors. Further complication may stem from the observation that, in some cases, there may be numbers of contributors that are incompatible with the set of alleles seen in the profile of a mixed crime stain, given the genotype of a potential contributor. In such situations, procedures that take a single and fixed number contributors as their output can lead to inferential impasses. Assessing the number of contributors within a probabilistic framework can help avoiding such complication. Using elements of decision theory, this paper analyses two strategies for inference on the number of contributors. One procedure is deterministic and focuses on the minimum number of contributors required to 'explain' an observed set of alleles. The other procedure is probabilistic using Bayes' theorem and provides a probability distribution for a set of numbers of contributors, based on the set of observed alleles as well as their respective rates of occurrence. The discussion concentrates on mixed stains of varying quality (i.e., different numbers of loci for which genotyping information is available). A so-called qualitative interpretation is pursued since quantitative information such as peak area and height data are not taken into account. The competing procedures are compared using a standard scoring rule that penalizes the degree of divergence between a given agreed value for N, that is the number of contributors, and the actual value taken by N. Using only modest assumptions and a discussion with reference to a casework example, this paper reports on analyses using simulation techniques and graphical models (i.e., Bayesian networks) to point out that setting the number of contributors to a mixed crime stain in probabilistic terms is, for the conditions assumed in this study, preferable to a decision policy that uses categoric assumptions about N.

Extreme prematurity and intra uterine growth restriction effects in brain network topology at school age

Higher risk for long-term behavioral and emotional sequelae, with attentional problems (with or without hyperactivity) is now becoming one of the hallmarks of extreme premature (EP) birth and birth after pregancy conditions leading to poor intra uterine growth restriction (IUGR) [1,2]. However, little is know so far about the neurostructural basis of these complexe brain functional abnormalities that seem to have their origins in early critical periods of brain development. The development of cortical axonal pathways happens in a series of sequential events. The preterm phase (24-36 post conecptional weeks PCW) is known for being crucial for growth of the thalamocortical fiber bundles as well as for the development of long projectional, commisural and projectional fibers [3]. Is it logical to expect, thus, that being exposed to altered intrauterine environment (altered nutrition) or to extrauterine environment earlier that expected, lead to alterations in the structural organization and, consequently, alter the underlying white matter (WM) structure. Understanding rate and variability of normal brain development, and detect differences from typical development may offer insight into the neurodevelopmental anomalies that can be imaged at later stages. Due to its unique ability to non-invasively visualize and quantify in vivo white matter tracts in the brain, in this study we used diffusion MRI (dMRI) tractography to derive brain graphs [4,5,6]. This relatively simple way of modeling the brain enable us to use graph theory to study topological properties of brain graphs in order to study the effects of EP and IUGR on childrens brain connectivity at age 6 years old.

Light intensity modulates the regulatory network of the shade avoidance response in Arabidopsis.

Plants such as Arabidopsis thaliana respond to foliar shade and neighbors who may become competitors for light resources by elongation growth to secure access to unfiltered sunlight. Challenges faced during this shade avoidance response (SAR) are different under a light-absorbing canopy and during neighbor detection where light remains abundant. In both situations, elongation growth depends on auxin and transcription factors of the phytochrome interacting factor (PIF) class. Using a computational modeling approach to study the SAR regulatory network, we identify and experimentally validate a previously unidentified role for long hypocotyl in far red 1, a negative regulator of the PIFs. Moreover, we find that during neighbor detection, growth is promoted primarily by the production of auxin. In contrast, in true shade, the system operates with less auxin but with an increased sensitivity to the hormonal signal. Our data suggest that this latter signal is less robust, which may reflect a cost-to-robustness tradeoff, a system trait long recognized by engineers and forming the basis of information theory.

The social disembedding of business theory and practice. A (neo-)institutional analysis of the homo economicus and corporate social responsibility, and the inherent responsibility of business scholars

Aim Structure of the Thesis In the first article, I focus on the context in which the Homo Economicus was constructed - i.e., the conception of economic actors as fully rational, informed, egocentric, and profit-maximizing. I argue that the Homo Economicus theory was developed in a specific societal context with specific (partly tacit) values and norms. These norms have implicitly influenced the behavior of economic actors and have framed the interpretation of the Homo Economicus. Different factors however have weakened this implicit influence of the broader societal values and norms on economic actors. The result is an unbridled interpretation and application of the values and norms of the Homo Economicus in the business environment, and perhaps also in the broader society. In the second article, I show that the morality of many economic actors relies on isomorphism, i.e., the attempt to fit into the group by adopting the moral norms surrounding them. In consequence, if the norms prevailing in a specific group or context (such as a specific region or a specific industry) change, it can be expected that actors with an 'isomorphism morality' will also adapt their ethical thinking and their behavior -for the 'better' or for the 'worse'. The article further describes the process through which corporations could emancipate from the ethical norms prevailing in the broader society, and therefore develop an institution with specific norms and values. These norms mainly rely on mainstream business theories praising the economic actor's self-interest and neglecting moral reasoning. Moreover, because of isomorphism morality, many economic actors have changed their perception of ethics, and have abandoned the values prevailing in the broader society in order to adopt those of the economic theory. Finally, isomorphism morality also implies that these economic actors will change their morality again if the institutional context changes. The third article highlights the role and responsibility of business scholars in promoting a systematic reflection and self-critique of the business system and develops alternative models to fill the moral void of the business institution and its inherent legitimacy crisis. Indeed, the current business institution relies on assumptions such as scientific neutrality and specialization, which seem at least partly challenged by two factors. First, self-fulfilling prophecy provides scholars with an important (even if sometimes undesired) normative influence over practical life. Second, the increasing complexity of today's (socio-political) world and interactions between the different elements constituting our society question the strong specialization of science. For instance, economic theories are not unrelated to psychology or sociology, and economic actors influence socio-political structures and processes, e.g., through lobbying (Dobbs, 2006; Rondinelli, 2002), or through marketing which changes not only the way we consume, but more generally tries to instill a specific lifestyle (Cova, 2004; M. K. Hogg & Michell, 1996; McCracken, 1988; Muniz & O'Guinn, 2001). In consequence, business scholars are key actors in shaping both tomorrow's economic world and its broader context. A greater awareness of this influence might be a first step toward an increased feeling of civic responsibility and accountability for the models and theories developed or taught in business schools.

Graph theory reveals dysconnected hubs in 22q11DS and altered nodal efficiency in patients with hallucinations.

Schizophrenia is postulated to be the prototypical dysconnection disorder, in which hallucinations are the core symptom. Due to high heterogeneity in methodology across studies and the clinical phenotype, it remains unclear whether the structural brain dysconnection is global or focal and if clinical symptoms result from this dysconnection. In the present work, we attempt to clarify this issue by studying a population considered as a homogeneous genetic sub-type of schizophrenia, namely the 22q11.2 deletion syndrome (22q11.2DS). Cerebral MRIs were acquired for 46 patients and 48 age and gender matched controls (aged 6-26, respectively mean age = 15.20 ± 4.53 and 15.28 ± 4.35 years old). Using the Connectome mapper pipeline (connectomics.org) that combines structural and diffusion MRI, we created a whole brain network for each individual. Graph theory was used to quantify the global and local properties of the brain network organization for each participant. A global degree loss of 6% was found in patients' networks along with an increased Characteristic Path Length. After identifying and comparing hubs, a significant loss of degree in patients' hubs was found in 58% of the hubs. Based on Allen's brain network model for hallucinations, we explored the association between local efficiency and symptom severity. Negative correlations were found in the Broca's area (p < 0.004), the Wernicke area (p < 0.023) and a positive correlation was found in the dorsolateral prefrontal cortex (DLPFC) (p < 0.014). In line with the dysconnection findings in schizophrenia, our results provide preliminary evidence for a targeted alteration in the brain network hubs' organization in individuals with a genetic risk for schizophrenia. The study of specific disorganization in language, speech and thought regulation networks sharing similar network properties may help to understand their role in the hallucination mechanism.