Hierarchical modelling of timber reference properties using probabilistic methods: Maximum Likelihood Method, Bayesian Methods and Probability Networks

In recent decades, an increased interest has been evidenced in the research on multi-scale hierarchical modelling in the field of mechanics, and also in the field of wood products and timber engineering. One of the main motivations for hierar-chical modelling is to understand how properties, composition and structure at lower scale levels may influence and be used to predict the material properties on a macroscopic and structural engineering scale. This chapter presents the applicability of statistic and probabilistic methods, such as the Maximum Likelihood method and Bayesian methods, in the representation of timber’s mechanical properties and its inference accounting to prior information obtained in different importance scales. These methods allow to analyse distinct timber’s reference properties, such as density, bending stiffness and strength, and hierarchically consider information obtained through different non, semi or destructive tests. The basis and fundaments of the methods are described and also recommendations and limitations are discussed. The methods may be used in several contexts, however require an expert’s knowledge to assess the correct statistic fitting and define the correlation arrangement between properties.

The AP-1 transcription factor c-Jun prevents stress-imposed maladaptive remodeling of the heart.

Systemic hypertension increases cardiac workload and subsequently induces signaling networks in heart that underlie myocyte growth (hypertrophic response) through expansion of sarcomeres with the aim to increase contractility. However, conditions of increased workload can induce both adaptive and maladaptive growth of heart muscle. Previous studies implicate two members of the AP-1 transcription factor family, junD and fra-1, in regulation of heart growth during hypertrophic response. In this study, we investigate the function of the AP-1 transcription factors, c-jun and c-fos, in heart growth. Using pressure overload-induced cardiac hypertrophy in mice and targeted deletion of Jun or Fos in cardiomyocytes, we show that c-jun is required for adaptive cardiac hypertrophy, while c-fos is dispensable in this context. c-jun promotes expression of sarcomere proteins and suppresses expression of extracellular matrix proteins. Capacity of cardiac muscle to contract depends on organization of principal thick and thin filaments, myosin and actin, within the sarcomere. In line with decreased expression of sarcomere-associated proteins, Jun-deficient cardiomyocytes present disarrangement of filaments in sarcomeres and actin cytoskeleton disorganization. Moreover, Jun-deficient hearts subjected to pressure overload display pronounced fibrosis and increased myocyte apoptosis finally resulting in dilated cardiomyopathy. In conclusion, c-jun but not c-fos is required to induce a transcriptional program aimed at adapting heart growth upon increased workload.

Dynamic simulation of regulatory networks using SQUAD.

BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.

Diffusion spectrum imaging shows the structural basis of functional cerebellar circuits in the human cerebellum in vivo.

BACKGROUND: The cerebellum is a complex structure that can be affected by several congenital and acquired diseases leading to alteration of its function and neuronal circuits. Identifying the structural bases of cerebellar neuronal networks in humans in vivo may provide biomarkers for diagnosis and management of cerebellar diseases. OBJECTIVES: To define the anatomy of intrinsic and extrinsic cerebellar circuits using high-angular resolution diffusion spectrum imaging (DSI). METHODS: We acquired high-resolution structural MRI and DSI of the cerebellum in four healthy female subjects at 3T. DSI tractography based on a streamline algorithm was performed to identify the circuits connecting the cerebellar cortex with the deep cerebellar nuclei, selected brainstem nuclei, and the thalamus. RESULTS: Using in-vivo DSI in humans we were able to demonstrate the structure of the following cerebellar neuronal circuits: (1) connections of the inferior olivary nucleus with the cerebellar cortex, and with the deep cerebellar nuclei (2) connections between the cerebellar cortex and the deep cerebellar nuclei, (3) connections of the deep cerebellar nuclei conveyed in the superior (SCP), middle (MCP) and inferior (ICP) cerebellar peduncles, (4) complex intersections of fibers in the SCP, MCP and ICP, and (5) connections between the deep cerebellar nuclei and the red nucleus and the thalamus. CONCLUSION: For the first time, we show that DSI tractography in humans in vivo is capable of revealing the structural bases of complex cerebellar networks. DSI thus appears to be a promising imaging method for characterizing anatomical disruptions that occur in cerebellar diseases, and for monitoring response to therapeutic interventions.

The role of population movement in the epidemiology and control of schistosomiasis in Brazil: a preliminary typology of population movement

This paper examines recent developments in migration studies. It reviews literature related to the potential role of internal population movement in the occurrence of schistosomiasis in Brazil and modifies Prothero's typology of population movement for use in Brazil. This modified classification system may contribute to a better understanding of schistosome transmission as well as improved research and control programs. The results of this study indicate that population movement in Brazil primarily involves economically-motivated rural-urban and interregional movement. However, several movement patterns have become increasingly important in recent years as a result of changing socioeconomic and urbanisation dynamics. These patterns include urban-urban, intracity and urban-rural movement as well as the movement of environmental refugees and tourists. Little is known about the epidemiological significance of these patterns. This paper also highlights the role of social networks in the decision to migrate and to settle. Prothero's classic population movement typology categorises movement as either one-way migrations or circulations and examines them along spatial and temporal scales. However, the typology must be modified as epidemiological information about new patterns becomes available. This paper identifies areas that require further research and offers recommendations that can improve the measurement and spatial analysis of the relationship between population movement and schistosomiasis.

Map of ecological networks for landscape planning

This paper presents a method based on a geographical information system (GIS) to model ecological networks in a fragmented landscape. The ecological networks are generated with the help of a landscape model (which integrate human activities) and with a wildlife dispersal model. The main results are maps which permit the analysis and the understanding of the impact of human activities on wildlife dispersal. Three applications in a study area are presented: ecological networks at the landscape scale, conflicting areas at the farmstead scale and ecological distance between biotopes. These applications show the flexibility of the model and its potential to give information on ecological networks at different planning scales.

Genetic clusters and sex-biased gene flow in a unicolonial Formica ant.

BACKGROUND: Animal societies are diverse, ranging from small family-based groups to extraordinarily large social networks in which many unrelated individuals interact. At the extreme of this continuum, some ant species form unicolonial populations in which workers and queens can move among multiple interconnected nests without eliciting aggression. Although unicoloniality has been mostly studied in invasive ants, it also occurs in some native non-invasive species. Unicoloniality is commonly associated with very high queen number, which may result in levels of relatedness among nestmates being so low as to raise the question of the maintenance of altruism by kin selection in such systems. However, the actual relatedness among cooperating individuals critically depends on effective dispersal and the ensuing pattern of genetic structuring. In order to better understand the evolution of unicoloniality in native non-invasive ants, we investigated the fine-scale population genetic structure and gene flow in three unicolonial populations of the wood ant F. paralugubris. RESULTS: The analysis of geo-referenced microsatellite genotypes and mitochondrial haplotypes revealed the presence of cryptic clusters of genetically-differentiated nests in the three populations of F. paralugubris. Because of this spatial genetic heterogeneity, members of the same clusters were moderately but significantly related. The comparison of nuclear (microsatellite) and mitochondrial differentiation indicated that effective gene flow was male-biased in all populations. CONCLUSION: The three unicolonial populations exhibited male-biased and mostly local gene flow. The high number of queens per nest, exchanges among neighbouring nests and restricted long-distance gene flow resulted in large clusters of genetically similar nests. The positive relatedness among clustermates suggests that kin selection may still contribute to the maintenance of altruism in unicolonial populations if competition occurs among clusters.

Drivers of human resource management competences development in Brazilian multinational subsidiaries: a multilevel research

This article aims to verify the factors associated with the development of human resource management (HRM) competences in foreign subsidiaries of Brazilian multinationals. These competences are essential in that they allow foreign units to adopt HRM practices that are consistent with the countries or markets in which they operate. A multilevel research was conducted, involving headquarters and subsidiaries of major Brazilian companies; the empirical analysis employed hierarchical linear modelling. Despite the recurrent debate on global standardisation versus local adaptation, it was identified that the integration of international HRM policies (addressing simultaneously global guidelines and local response) may stimulate competences development. In addition, interaction in external networks in the host country may enhance the development of HRM competences in the subsidiaries. However, specific cultural factors of the company may inhibit development activity in units abroad.

Discriminant validity and test-retest reliability of a self-administered Internet-based questionnaire testing doctors' knowledge in evidence-based medicine.

Aims and objectives  This study aimed to determine the discriminant validity and the test-retest reliability of a questionnaire testing the impact of evidence-based medicine (EBM) training on doctors' knowledge and skills. Methods  Questionnaires were sent electronically to all doctors working as residents and chief residents in two French speaking hospital networks in Switzerland. Participants completed the questionnaire twice, within a 4-week interval. The discriminant validity was examined in comparing doctors' performance according to their reported EBM previous training. Proportion of agreement between both sessions of the questionnaire, Cohen's kappa and 'uniform kappa' determined its test-retest reliability. Results  The participation rate was 9.8%/7.1% to first/second session. Performance increased according to the level of doctors' previous training in EBM. The observed proportion of agreement between both sessions was over 70% for 14/19 questions, and the 'uniform kappa' was superior to 0.60 for 15/19 questions. Conclusion  The discriminant validity and test-retest reliability of the questionnaire were satisfying. The low participation rate did not prevent the study from achieving its aims.

Bristle pattern formation in the thorax formation of Drosophila: a systems level approach

A fundamental question in developmental biology is how tissues are patterned to give rise to differentiated body structures with distinct morphologies. The Drosophila wing disc offers an accessible model to understand epithelial spatial patterning. It has been studied extensively using genetic and molecular approaches. Bristle patterns on the thorax, which arise from the medial part of the wing disc, are a classical model of pattern formation, dependent on a pre-pattern of trans-activators and –repressors. Despite of decades of molecular studies, we still only know a subset of the factors that determine the pre-pattern. We are applying a novel and interdisciplinary approach to predict regulatory interactions in this system. It is based on the description of expression patterns by simple logical relations (addition, subtraction, intersection and union) between simple shapes (graphical primitives). Similarities and relations between primitives have been shown to be predictive of regulatory relationships between the corresponding regulatory factors in other Systems, such as the Drosophila egg. Furthermore, they provide the basis for dynamical models of the bristle-patterning network, which enable us to make even more detailed predictions on gene regulation and expression dynamics. We have obtained a data-set of wing disc expression patterns which we are now processing to obtain average expression patterns for each gene. Through triangulation of the images we can transform the expression patterns into vectors which can easily be analysed by Standard clustering methods. These analyses will allow us to identify primitives and regulatory interactions. We expect to identify new regulatory interactions and to understand the basic Dynamics of the regulatory network responsible for thorax patterning. These results will provide us with a better understanding of the rules governing gene regulatory networks in general, and provide the basis for future studies of the evolution of the thorax-patterning network in particular.

Small and long non-coding RNAs in cardiac homeostasis and regeneration

Cardiovascular diseases and in particular heart failure are major causes of morbidity and mortality in the Western world. Recently, the notion of promoting cardiac regeneration as a means to replace lost cardiomyocytes in the damaged heart has engendered considerable research interest. These studies envisage the utilization of both endogenous and exogenous cellular populations, which undergo highly specialized cell fate transitions to promote cardiomyocyte replenishment. Such transitions are under the control of regenerative gene regulatory networks, which are enacted by the integrated execution of specific transcriptional programs. In this context, it is emerging that the non-coding portion of the genome is dynamically transcribed generating thousands of regulatory small and long non-coding RNAs, which are central orchestrators of these networks. In this review, we discuss more particularly the biological roles of two classes of regulatory non-coding RNAs, i.e. microRNAs and long non-coding RNAs, with a particular emphasis on their known and putative roles in cardiac homeostasis and regeneration. Indeed, manipulating non-coding RNA-mediated regulatory networks could provide keys to unlock the dormant potential of the mammalian heart to regenerate. This should ultimately improve the effectiveness of current regenerative strategies and discover new avenues for repair. This article is part of a Special Issue entitled: Cardiomyocyte Biology: Cardiac Pathways of Differentiation, Metabolism and Contraction.

Gendered networks and Mexican migration

In this paper, we investigate how the gendered origin of migrant networks (i.e. matrilineal vs. patrilineal) is associated with aspirations to migrate and subsequent migration behavior. Using longitudinal data from the Mexican Family Life Survey (MxFLS), we follow 3,923 married couples across 139 municipalities over the 2002-2005 period. We find that the networks of both the individual and her/his spouse are associated with aspiring to migrate to the United States. However, one’s own network matters most (i.e. matrilineal networks for women and patrilineal networks for men). On the other hand, in terms of behavior, only matrilineal networks predict a subsequent move to the U.S. for men and women/couples, who are assessed jointly. These findings suggest that our understanding of the role of migrant networks in perpetuating male-centered, labor migration does not necessarily translate once a union has formed. We make the case that future work would do well to account for not only the presence and composition of networks, but also their origin, which in certain circumstances may be the most relevant factor.

Towards robust network based complex systems : from evolutionary cellular automata to biological models

Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

Completing contracts ex post: How car manufacturers manage car dealers

This article illustrates how contracts are completed ex post in practice and, in so doing, indirectly suggests what the real function of contracts may be. Our evidence comes from the contracts between automobile manufacturers and their dealers in 23 dealership networks in Spain. Franchising dominates automobile distribution because of the need to decentralize pricing and control of service decisions. It motivates local managers to undertake these activities at minimum cost for the manufacturer. However, it creates incentive conflicts, both between manufacturers and dealers and among dealers themselves, concerning the level of sales and service provided. It also holds potential for expropriation of specific investments. Contracts deal with these conflicts by restricting dealers decision rights and granting manufacturers extensive completion, monitoring and enforcement powers. The main mechanism that may prevent abuse of these powers is the manufacturers reputational capital.

Class of correlated random networks with hidden variables

We study a class of models of correlated random networks in which vertices are characterized by hidden variables controlling the establishment of edges between pairs of vertices. We find analytical expressions for the main topological properties of these models as a function of the distribution of hidden variables and the probability of connecting vertices. The expressions obtained are checked by means of numerical simulations in a particular example. The general model is extended to describe a practical algorithm to generate random networks with an a priori specified correlation structure. We also present an extension of the class, to map nonequilibrium growing networks to networks with hidden variables that represent the time at which each vertex was introduced in the system.