Baboon (Papio anubis) social complexity--a network approach

Although many studies have analyzed the causes and consequences of social relationships, few studies have explicitly assessed how measures of social relationships are affected by the choice of behaviors used to quantify them. The use of many behaviors to measure social relationships in primates has long been advocated, but it was analytically difficult to implement this framework into primatological work. However, recent advances in social network analysis (SNA) now allow the comparison of multiple networks created from different behaviors. Here we use our database of baboon social behavior (Papio anubis, Gashaka Gumti National Park, Nigeria) to investigate (i) to what extent social networks created from different behaviors overlap, (ii) to what extent individuals occupy similar social positions in these networks and (iii) how sex affects social network position in this population of baboons. We used data on grooming, aggression, displacement, mounting and presenting, which were collected over a 15-month period. We calculated network parameters separately for each behavior. Networks based on displacement, mounting and presenting were very similar to each other, whereas grooming and aggression networks differed both from each other and from mounting, displacement and presenting networks. Overall, individual network positions were strongly affected by sex. Individuals central in one network tended to be central in most other networks as well, whereas other measures such as clustering coefficient were found to vary depending on the behavior analyzed. Thus, our results suggest that a baboon's social environment is best described by a multiplex network based on affiliative, aggressive and sexual behavior. Modern SNA provides a number of useful tools that will help us to better understand animals' social environment. We also discuss potential caveats related to their use.     

Space to choose: network analysis of social preferences in a captive chimpanzee community, and implications for management

Social network analysis (SNA) is rapidly gaining popularity in primatology, but its application to the management of zoo-housed primates has been largely overlooked. Here I use SNA techniques to explore the social structure of chimpanzees (Pan troglodytes) housed in the new "Budongo Trail" exhibit at Edinburgh Zoo, UK. Given that individuals have extensive space (2332 m(2)), and access to several interconnected exhibit sections, I test the hypothesis that individuals are able to choose to interact with specific social partners. Spatial association and social interaction data were recorded from 400 focal watches on 11 individuals, and association, affiliative, and agonistic networks were constructed. Matrix correlations showed that individuals who spent time in close proximity were likely to affiliate with one another, but spatial association did not predict the frequency of agonistic encounters. Cluster analysis revealed significantly distinct sub-groups in the affiliative network (but not association or agonistic networks) in line with maternal kinship. Overall my findings support the hypothesis that the Budongo Trail exhibit facilitates the expression of social preferences, and suggests that SNA can be a useful tool to study zoo primates when proximity between individuals is not forced (i.e. in large, modern exhibits). Now that I have validated a set of SNA methods for this community, they can be used to trace changes in social dynamics over a longer time period, and ultimately assist zoo staff in their management decisions.     

Understanding the Organization of Industrial Ecosystems

Industrial symbiosis (IS) has been used to describe the physical exchange and shared management of input and output materials by geographically proximate firms. Firms that engage in IS are said to belong to an industrial ecosystem. Symbiosis has been found to be motivated by economic considerations, such as lowering costs for waste disposal, as well as by environmental ones, such as accessing limited water supplies. Communication and trust among managers are thought to play important roles in exchanges; however, empirical studies have not been previously conducted. This study used social network analysis (SNA) to identify the prevalence of industrial symbiosis linkages in Barceloneta, Puerto Rico. The study quantified patterns in various relationships among firms and managers, including formal relations through supply chains, and informal ones through interpersonal interactions. SNA and statistical methods were used to explore how these ties correlate with observed industrial symbiosis activities. IS linkages were found to be less prevalent than product sales among firms and were concentrated among pharmaceutical firms at the core of the regional network. Trust among managers and position in the social hierarchy were found to be correlated with IS but not supply chain links. SNA was useful for examining the organization of different relationships in the industrial ecosystem, but contextual information is still needed to add meaning to its findings.     

He Votes or She Votes? Female and Male Discursive Strategies in Twitter Political Hashtags

In this paper, we conduct a study about differences between female and male discursive strategies when posting in the microblogging service Twitter, with a particular focus on the hashtag designation process during political debate. The fact that men and women use language in distinct ways, reverberating practices linked to their expected roles in the social groups, is a linguistic phenomenon known to happen in several cultures and that can now be studied on the Web and on online social networks in a large scale enabled by computing power. Here, for instance, after analyzing tweets with political content posted during Brazilian presidential campaign,we found out that male Twitter users, when expressing their attitude toward a given candidate, are more prone to use imperative verbal forms in hashtags, while female users tend to employ declarative forms. This difference can be interpreted as a sign of distinct approaches in relation to other network members: for example, if political hashtags are seen as strategies of persuasion in Twitter, imperative tags could be understood as more overt ways of persuading and declarative tags as more indirect ones. Our findings help to understand human gendered behavior in social networks and contribute to research on the new fields of computer-enabled Internet linguistics and social computing, besides being useful for several computational tasks such as developing tag recommendation systems based on users'' collective preferences and tailoring targeted advertising strategies, among others.     

Social Semantic Web Framework for Industrial Synergies Initiation

Industrial synergies join two or more organizations that initially functioned as independent economic actors—that may originate from different sectors—together in order to share resources and exchange by‐products for mutual environmental, financial, and social benefits for its participants. Industrial symbioses (ISs) are networks of industrial synergies that can be initiated and created over time in various manners. In practice, the initiation of an industrial synergy, and particularly the identification of by‐product compatibilities, relies on direct or facilitated knowledge and information sharing, which is essential for discovering industrial synergy opportunities. Beyond its potential contribution to facilitate knowledge and information sharing among organizations, the Social Semantic Web (SSW) also has the potential to facilitate the initiation of industrial synergy by systematically and automatically identifying and recommending by‐products exchange compatibilities to potential partners. This framework exploits the ability of the sematic web to enable the search for analogies between potential partners within a region or district and existing industrial synergies around the world. This paper proposes the Social Semantic Web for Industrial Synergies Initiation (SSWISI) framework for the initiation of industrial synergies, which is based on the Social Semantic Web. The framework proposed in this paper adopts the concept of Linked Open Data (LOD), which enables the sharing and exchanging of information with external systems. This feature distinguishes the proposed framework from the existing approaches in its initiation of industrial synergies.     

Bistability and oscillations in chemical reaction networks

Bifurcation theory is one of the most widely used approaches for analysis of dynamical behaviour of chemical and biochemical reaction networks. Some of the interesting qualitative behaviour that are analyzed are oscillations and bistability (a situation where a system has at least two coexisting stable equilibria). Both phenomena have been identified as central features of many biological and biochemical systems. This paper, using the theory of stoichiometric network analysis (SNA) and notions from algebraic geometry, presents sufficient conditions for a reaction network to display bifurcations associated with these phenomena. The advantage of these conditions is that they impose fewer algebraic conditions on model parameters than conditions associated with standard bifurcation theorems. To derive the new conditions, a coordinate transformation will be made that will guarantee the existence of branches of positive equilibria in the system. This is particularly useful in mathematical biology, where only positive variable values are considered to be meaningful. The first part of the paper will be an extended introduction to SNA and algebraic geometry-related methods which are used in the coordinate transformation and set up of the theorems. In the second part of the paper we will focus on the derivation of bifurcation conditions using SNA and algebraic geometry. Conditions will be derived for three bifurcations: the saddle-node bifurcation, a simple branching point, both linked to bistability, and a simple Hopf bifurcation. The latter is linked to oscillatory behaviour. The conditions derived are sufficient and they extend earlier results from stoichiometric network analysis as can be found in (Aguda and Clarke in J Chem Phys 87:3461–3470, 1987; Clarke and Jiang in J Chem Phys 99:4464–4476, 1993; Gatermann et al. in J Symb Comput 40:1361–1382, 2005). In these papers some necessary conditions for two of these bifurcations were given. A set of examples will illustrate that algebraic conditions arising from given sufficient bifurcation conditions are not more difficult to interpret nor harder to calculate than those arising from necessary bifurcation conditions. Hence an increasing amount of information is gained at no extra computational cost. The theory can also be used in a second step for a systematic bifurcation analysis of larger reaction networks. We have added a dedication of the paper to K. Gatermann.     

What sets the long-term level of sympathetic nerve activity: is there a role for arterial baroreceptors?

Much of our knowledge of the influence of the sympathetic nervous system on the control of blood pressure is built on experimental approaches that focus very much on time scales <24 h. Although direct recordings of sympathetic nerve activity (SNA) over short time scales provide important information, it is difficult to place their relevance over the longer term where the development of chronic changes in blood pressure are likely to be a mixture of hormonal, renal, and neural influences. Recently new experimental approaches are now revealing a possible role for arterial baroreceptors in the chronic regulation of SNA. These studies reveal that chronic increases in blood pressure are associated with chronic changes in SNA that may be due to nonresetting of the blood pressure-SNA baroreflex relationship. This review discusses the implications of such information, highlighting new technologies for long-term recording of SNA that appear to hold much promise for revealing the role of SNA to the kidney for the long-term control of blood pressure.     

Network compression as a quality measure for protein interaction networks

With the advent of large-scale protein interaction studies, there is much debate about data quality. Can different noise levels in the measurements be assessed by analyzing network structure? Because proteomic regulation is inherently co-operative, modular and redundant, it is inherently compressible when represented as a network. Here we propose that network compression can be used to compare false positive and false negative noise levels in protein interaction networks. We validate this hypothesis by first confirming the detrimental effect of false positives and false negatives. Second, we show that gold standard networks are more compressible. Third, we show that compressibility correlates with co-expression, co-localization, and shared function. Fourth, we also observe correlation with better protein tagging methods, physiological expression in contrast to over-expression of tagged proteins, and smart pooling approaches for yeast two-hybrid screens. Overall, this new measure is a proxy for both sensitivity and specificity and gives complementary information to standard measures such as average degree and clustering coefficients.     

Polynomial-Time Algorithm for Controllability Test of a Class of Boolean Biological Networks

In recent years, Boolean-network-model-based approaches to dynamical analysis of complex biological networks such as gene regulatory networks have been extensively studied. One of the fundamental problems in control theory of such networks is the problem of determining whether a given substance quantity can be arbitrarily controlled by operating the other substance quantities, which we call the controllability problem. This paper proposes a polynomial-time algorithm for solving this problem. Although the algorithm is based on a sufficient condition for controllability, it is easily computable for a wider class of large-scale biological networks compared with the existing approaches. A key to this success in our approach is to give up computing Boolean operations in a rigorous way and to exploit an adjacency matrix of a directed graph induced by a Boolean network. By applying the proposed approach to a neurotransmitter signaling pathway, it is shown that it is effective.     

Unraveling the signal scenario of fruit set

Long-term goals to impact or modify fruit quality and yield have been the target of researchers for many years. Different approaches such as traditional breeding, mutation breeding, and transgenic approaches have revealed a regulatory network where several hormones concur in a complex way to regulate fruit set and development, and these networks are shared in some way among species with different kinds of fruits. Understanding the molecular and biochemical networks of fruit set and development could be very useful for breeders to meet the current and future challenges of agricultural problems.     

Game Theoretical Analysis on Cooperation Stability and Incentive Effectiveness in Community Networks

Community networks, the distinguishing feature of which is membership admittance, appear on P2P networks, social networks, and conventional Web networks. Joining the network costs money, time or network bandwidth, but the individuals get access to special resources owned by the community in return. The prosperity and stability of the community are determined by both the policy of admittance and the attraction of the privileges gained by joining. However, some misbehaving users can get the dedicated resources with some illicit and low-cost approaches, which introduce instability into the community, a phenomenon that will destroy the membership policy. In this paper, we analyze on the stability using game theory on such a phenomenon. We propose a game-theoretical model of stability analysis in community networks and provide conditions for a stable community. We then extend the model to analyze the effectiveness of different incentive policies, which could be used when the community cannot maintain its members in certain situations. Then we verify those models through a simulation. Finally, we discuss several ways to promote community network’s stability by adjusting the network’s properties and give some proposal on the designs of these types of networks from the points of game theory and stability.     

Life Sciences and the web: a new era for collaboration

The World Wide Web has revolutionized how researchers from various disciplines collaborate over long distances. This is nowhere more important than in the Life Sciences, where interdisciplinary approaches are becoming increasingly powerful as a driver of both integration and discovery. Data access, data quality, identity, and provenance are all critical ingredients to facilitate and accelerate these collaborative enterprises and it is here where Semantic Web technologies promise to have a profound impact. This paper reviews the need for, and explores advantages of as well as challenges with these novel Internet information tools as illustrated with examples from the biomedical community.     

Assessing Social Networks in Patients with Psychotic Disorders: A Systematic Review of Instruments

Background

Evidence suggests that social networks of patients with psychotic disorders influence symptoms, quality of life and treatment outcomes. It is therefore important to assess social networks for which appropriate and preferably established instruments should be used.

Aims

To identify instruments assessing social networks in studies of patients with psychotic disorders and explore their properties.

Method

A systematic search of electronic databases was conducted to identify studies that used a measure of social networks in patients with psychotic disorders.

Results

Eight instruments were identified, all of which had been developed before 1991. They have been used in 65 studies (total N of patients = 8,522). They assess one or more aspects of social networks such as their size, structure, dimensionality and quality. Most instruments have various shortcomings, including questionable inter-rater and test-retest reliability.

Conclusions

The assessment of social networks in patients with psychotic disorders is characterized by a variety of approaches which may reflect the complexity of the construct. Further research on social networks in patients with psychotic disorders would benefit from advanced and more precise instruments using comparable definitions of and timescales for social networks across studies.     

Content Delivery Policies in Replicated Web Services: Client-Side vs. Server-Side

Replication of Web Services has an important role among techniques that have been developed in order to meet the demand for faster and more efficient access to the Internet. Replication can be addressed both by a cluster of servers, and by servers geographically distributed in the Internet. In this paper, we focus on geographical replication. Two approaches are commonly used for geographical replication: server-side and client-side. In the client-side approach, the client has a significant role in the policy used to exploit Web Service Replication. In the server-side approach, the client transparently exploits a Replicated Web Service. Both server-side and client-side approaches provide various strategies that can be adopted. An analysis of these strategies, and an overall classification, is presented here. Finally, client-side and server-side approaches are compared, identifying their pros and cons in order to propose the features of an eventual complete approach.     

Evolutionary Medicine and the Medical School Curriculum: Meeting Students Along Their Paths to Medical School

Over the past several years, numerous reports that have been independently prepared by prestigious organizations in the U.S. have agreed that new approaches to improve teaching and learning of biology at both the pre-college and undergraduate levels are important and timely. Their recommendations, which are based on emerging research about human learning and cognition, are in agreement that evolution is an organizing principle and foundation of modern biology and should be presented as such. This paper provides an overview of the conclusions and recommendations from those reports and proposes that helping students learn evolution through the lens of human examples that are part of the emerging field of evolutionary medicine could help biology educators improve the teaching of evolution, and biology more generally, by asking students to address biological problems that are inherently interesting and motivating.