Women Favour Dyadic Relationships,but Men Prefer Clubs: Cross-Cultural Evidence from Social Networking

The ability to create lasting, trust-based friendships makes it possible for humans to form large and coherent groups. The recent literature on the evolution of sociality and on the network dynamics of human societies suggests that large human groups have a layered structure generated by emotionally supported social relationships. There are also gender differences in adult social style which may involve different trade-offs between the quantity and quality of friendships. Although many have suggested that females tend to focus on intimate relations with a few other females, while males build larger, more hierarchical coalitions, the existence of such gender differences is disputed and data from adults is scarce. Here, we present cross-cultural evidence for gender differences in the preference for close friendships. We use a sample of ∼112,000 profile pictures from nine world regions posted on a popular social networking site to show that, in self-selected displays of social relationships, women favour dyadic relations, whereas men favour larger, all-male cliques. These apparently different solutions to quality-quantity trade-offs suggest a universal and fundamental difference in the function of close friendships for the two sexes.     

ISART: A Generic Framework for Searching Books with Social Information

Effective book search has been discussed for decades and is still future-proof in areas as diverse as computer science, informatics, e-commerce and even culture and arts. A variety of social information contents (e.g, ratings, tags and reviews) emerge with the huge number of books on the Web, but how they are utilized for searching and finding books is seldom investigated. Here we develop an Integrated Search And Recommendation Technology (IsArt), which breaks new ground by providing a generic framework for searching books with rich social information. IsArt comprises a search engine to rank books with book contents and professional metadata, a Generalized Content-based Filtering model to thereafter rerank books with user-generated social contents, and a learning-to-rank technique to finally combine a wide range of diverse reranking results. Experiments show that this technology permits embedding social information to promote book search effectiveness, and IsArt, by making use of it, has the best performance on CLEF/INEX Social Book Search Evaluation datasets of all 4 years (from 2011 to 2014), compared with some other state-of-the-art methods.     

ECO: A Generic Eutrophication Model Including Comprehensive Sediment-Water Interaction

The content and calibration of the comprehensive generic 3D eutrophication model ECO for water and sediment quality is presented. Based on a computational grid for water and sediment, ECO is used as a tool for water quality management to simulate concentrations and mass fluxes of nutrients (N, P, Si), phytoplankton species, detrital organic matter, electron acceptors and related substances. ECO combines integral simulation of water and sediment quality with sediment diagenesis and closed mass balances. Its advanced process formulations for substances in the water column and the bed sediment were developed to allow for a much more dynamic calculation of the sediment-water exchange fluxes of nutrients as resulting from steep concentration gradients across the sediment-water interface than is possible with other eutrophication models. ECO is to more accurately calculate the accumulation of organic matter and nutrients in the sediment, and to allow for more accurate prediction of phytoplankton biomass and water quality in response to mitigative measures such as nutrient load reduction. ECO was calibrated for shallow Lake Veluwe (The Netherlands). Due to restoration measures this lake underwent a transition from hypertrophic conditions to moderately eutrophic conditions, leading to the extensive colonization by submerged macrophytes. ECO reproduces observed water quality well for the transition period of ten years. The values of its process coefficients are in line with ranges derived from literature. ECO’s calculation results underline the importance of redox processes and phosphate speciation for the nutrient return fluxes. Among other things, the results suggest that authigenic formation of a stable apatite-like mineral in the sediment can contribute significantly to oligotrophication of a lake after a phosphorus load reduction.     

A Generic Shallow Lake Ecosystem Model Based on Collective Expert Knowledge

We used fuzzy cognitive mapping (FCM) to develop a generic shallow lake ecosystem model by augmenting the individual cognitive maps drawn by 8 scientists working in the area of shallow lake ecology. We calculated graph theoretical indices of the individual cognitive maps and the collective cognitive map produced by augmentation. There were a total of 32 variables with 113 connections in the collective cognitive map. The graph theoretical indices revealed internal cycles showing non-linear dynamics in the shallow lake ecosystem. The ecological processes were organized democratically without a top-down hierarchical structure. The most central variable in the collective map was submerged plants. The strongest connections were suspended solids concentration decreasing water clarity, phosphorus concentration increasing the phytoplankton biomass, higher water clarity increasing submerged plants, benthivorous fish biomass reducing submerged plants and increasing suspended solids concentration, and submerged plants decreasing suspended solids. The steady state condition of the generic model was a characteristic turbid shallow lake ecosystem. The generic shallow lake ecosystem model had the tendency to go into a turbid state since there were no dynamic environmental changes that could cause shifts between a turbid and a clearwater state, and the generic model indicated that only a dynamic disturbance regime could maintain the clearwater state. The model developed herein captured the empirical behavior of shallow lakes, and contained the basic model of the Alternative Stable States Theory. In addition, our model expanded the basic model by quantifying the relative effects of connections and by extending it with 22 more variables and 99 more weighted causal connections. Using our expanded model we ran 4 simulations: harvesting submerged plants, nutrient reduction, fish removal without nutrient reduction, and biomanipulation. Only biomanipulation, which included fish removal and nutrient reduction, had the potential to shift the turbid state into clearwater state. The structure and relationships in the generic model as well as the outcomes of the management simulations were supported by actual field studies in shallow lake ecosystems. Thus, fuzzy cognitive mapping methodology enabled us to understand the complex structure of shallow lake ecosystems as a whole and obtain a valid generic model based on tacit knowledge of experts in the field.     

Social Relationships and Mortality Risk: A Meta-analytic Review

Background

The quality and quantity of individuals'' social relationships has been linked not only to mental health but also to both morbidity and mortality.

Objectives

This meta-analytic review was conducted to determine the extent to which social relationships influence risk for mortality, which aspects of social relationships are most highly predictive, and which factors may moderate the risk.

Data Extraction

Data were extracted on several participant characteristics, including cause of mortality, initial health status, and pre-existing health conditions, as well as on study characteristics, including length of follow-up and type of assessment of social relationships.

Results

Across 148 studies (308,849 participants), the random effects weighted average effect size was OR = 1.50 (95% CI 1.42 to 1.59), indicating a 50% increased likelihood of survival for participants with stronger social relationships. This finding remained consistent across age, sex, initial health status, cause of death, and follow-up period. Significant differences were found across the type of social measurement evaluated (p<0.001); the association was strongest for complex measures of social integration (OR = 1.91; 95% CI 1.63 to 2.23) and lowest for binary indicators of residential status (living alone versus with others) (OR = 1.19; 95% CI 0.99 to 1.44).

Conclusions

The influence of social relationships on risk for mortality is comparable with well-established risk factors for mortality. Please see later in the article for the Editors'' Summary     

A Generic Crystallization-like Model That Describes the Kinetics of Amyloid Fibril Formation

Associated with neurodegenerative disorders such as Alzheimer, Parkinson, or prion diseases, the conversion of soluble proteins into amyloid fibrils remains poorly understood. Extensive "in vitro" measurements of protein aggregation kinetics have been reported, but no consensus mechanism has emerged until now. This contribution aims at overcoming this gap by proposing a theoretically consistent crystallization-like model (CLM) that is able to describe the classic types of amyloid fibrillization kinetics identified in our literature survey. Amyloid conversion represented as a function of time is shown to follow different curve shapes, ranging from sigmoidal to hyperbolic, according to the relative importance of the nucleation and growth steps. Using the CLM, apparently unrelated data are deconvoluted into generic mechanistic information integrating the combined influence of seeding, nucleation, growth, and fibril breakage events. It is notable that this complex assembly of interdependent events is ultimately reduced to a mathematically simple model, whose two parameters can be determined by little more than visual inspection. The good fitting results obtained for all cases confirm the CLM as a good approximation to the generalized underlying principle governing amyloid fibrillization. A perspective is presented on possible applications of the CLM during the development of new targets for amyloid disease therapeutics.     

Control of anaerobic digesters using Generic Model Control

This paper describes the improved effluent control of industrial anaerobic digestion treatment systems. Previous research has shown the possibility of applying a model-based adaptive control technique to these processes. This paper reviews this technique and shows that improved controllability can be obtained by a modification to the existing algorithm, based on a new control technique known as Generic Model Control, that simplifies and improves the robustness of the control algorithm.     

The Social Behaviour of Wild and Domestic Rattus norvegicus in Dyadic Encounters

The social behavour of trapped wild rats, laboratory-bred descendants of wild rats, and agouti laboratory rats, all Rattus norvegicus , was compared in encounters between pairs of adult males. Pairs of rats of the same type shared a large cage divided by a partition, which was removed at the beginning of each 20 minute observation period. Ten defined categories of behaviour were recorded. The Wild rats Attacked and Threatened and Ran Away more often than the other groups, while the Agoutis were generally more active, especially in investigatory behaviour, and maintained their initial levels of activity in the second encounter. The third group was intermediate in most respects. These findings are related to differences in genotype and environment.     

A Generic Model to Solve Tactical Planning Problems in Flexible Manufacturing Systems

This paper is an attempt to develop a generic modeling framework that addresses tactical planning problems of flexible manufacturing systems in a coherent manner. We propose a generic 0-1 mixed integer programming formulation, that integrates batching, loading, and routing problems with their critical aspects related to a system's performance. For this purpose, a thorough analysis is made to determine and relate system components, their attributes, and alternatives together with performance measures specific to tactical planning. This provided the justification to support our argument about generality of the model. A linear programming formulation is provided to approximate the mixed integer formulation proposed so as to overcome the problem's combinatorial complexity. The potential capability of the linear approximation proposed also is demonstrated via a small set of test problems.     

A Generic Model to Simulate Air-Borne Diseases as a Function of Crop Architecture

In a context of pesticide use reduction, alternatives to chemical-based crop protection strategies are needed to control diseases. Crop and plant architectures can be viewed as levers to control disease outbreaks by affecting microclimate within the canopy or pathogen transmission between plants. Modeling and simulation is a key approach to help analyze the behaviour of such systems where direct observations are difficult and tedious. Modeling permits the joining of concepts from ecophysiology and epidemiology to define structures and functions generic enough to describe a wide range of epidemiological dynamics. Additionally, this conception should minimize computing time by both limiting the complexity and setting an efficient software implementation. In this paper, our aim was to present a model that suited these constraints so it could first be used as a research and teaching tool to promote discussions about epidemic management in cropping systems. The system was modelled as a combination of individual hosts (population of plants or organs) and infectious agents (pathogens) whose contacts are restricted through a network of connections. The system dynamics were described at an individual scale. Additional attention was given to the identification of generic properties of host-pathogen systems to widen the model''s applicability domain. Two specific pathosystems with contrasted crop architectures were considered: ascochyta blight on pea (homogeneously layered canopy) and potato late blight (lattice of individualized plants). The model behavior was assessed by simulation and sensitivity analysis and these results were discussed against the model ability to discriminate between the defined types of epidemics. Crop traits related to disease avoidance resulting in a low exposure, a slow dispersal or a de-synchronization of plant and pathogen cycles were shown to strongly impact the disease severity at the crop scale.     

Experimental Models of the Dyadic Operant Behavior of Rats in Different Social Contexts

Biology Bulletin - To date, a number of methods for and approaches to the study of animal social behavior are used in ethology and neurophysiology. The present study describes experimental models...     

A Model of Human Cooperation in Social Dilemmas

Social dilemmas are situations in which collective interests are at odds with private interests: pollution, depletion of natural resources, and intergroup conflicts, are at their core social dilemmas. Because of their multidisciplinarity and their importance, social dilemmas have been studied by economists, biologists, psychologists, sociologists, and political scientists. These studies typically explain tendency to cooperation by dividing people in proself and prosocial types, or appealing to forms of external control or, in iterated social dilemmas, to long-term strategies. But recent experiments have shown that cooperation is possible even in one-shot social dilemmas without forms of external control and the rate of cooperation typically depends on the payoffs. This makes impossible a predictive division between proself and prosocial people and proves that people have attitude to cooperation by nature. The key innovation of this article is in fact to postulate that humans have attitude to cooperation by nature and consequently they do not act a priori as single agents, as assumed by standard economic models, but they forecast how a social dilemma would evolve if they formed coalitions and then they act according to their most optimistic forecast. Formalizing this idea we propose the first predictive model of human cooperation able to organize a number of different experimental findings that are not explained by the standard model. We show also that the model makes satisfactorily accurate quantitative predictions of population average behavior in one-shot social dilemmas.     

Social Relationships in Free-Ranging Male Macaca arctoides

Macaque social relationships differ greatly between species. Based on captive studies that focus mainly on females, researchers have classified stumptail macaque (Macaca arctoides) social relationships as tolerant, as indicated by a high rate of affiliation, frequent aggression, and symmetrical conflicts. To accumulate more data on male social relationships, which are relatively understudied, and to generate comparative data, we investigated male social relationships in a provisioned group of 68 free-ranging, naturally dispersing stumptail macaques in southern Thailand. We collected continuous focal animal and ad libitum data on 7 adult and 2 subadult males, recording social behavior during 283 contact hours between December 2006 and March 2007. Stumptail macaques of this population were less tolerant than predicted based on previous studies on captive groups: Rates of spatial proximity, affiliation, and aggression were low, most males directed affiliative behavior toward higher-ranking males, and conflicts were generally of low intensity and relatively asymmetrical. Thus, male stumptail macaques of the focal group appear to differ in their social style from a previous study of a captive group that mainly comprised of females. In some traits, they are even more intolerant than rhesus macaques, an intensively studied intolerant macaque species. We also compare our data on stumptail macaque males to those on other male macaques, but available data are too sparse to draw final conclusions.     

Social Relationships in a Group of Captive Wolves

The social organization of a group of wolves in a large outdoorenclosure was followed through several breeding seasons. Duringthe breeding season conflicts become more frequent and the socialhierarchy obvious. The more dominant animals restrict courtshipactivities by inferior wolves of their own sex. However, apparentlyas a correlate of their position, two alpha males have shownless mating activity than other males. Mate preferences exhibitedby animals of both sexes also limit the number of matings. Thepreferences appear related to the social hierarchy existingwhen an animal matures. Cultural transmission of social statusis suggested by some changes in ranking of wolves raised inthe woods at Brookfield. Temporary removal of the original alphamale and death of the original alpha female appear to have promotedchanges in social order and an increase in actual mating combinations.The probable consanguineous nature of wolf groups and facetsof the social behavior suggest that some form of group selectioncould be operative in the wild.     

BasinBox: A Generic Multimedia Fate Model for Predicting the Fate of Chemicals in River Catchments

Multimedia fate models have proven to be very useful tools in chemical risk assessment and management. This paper presents BasinBox, a newly developed steady-state generic multimedia fate model for evaluating risks of new and existing chemicals in river basins. The model concepts, as well as the intermedia processes quantified in the model, are outlined, and an overview of the required input parameters is given. To test the BasinBox model, calculations were carried out for predicting the fate of chemicals in the river Rhine basin. This was done for a set of 3175 hypothetical chemicals and three emission scenarios to air, river water and cropland soils. For each of these hypothetical chemicals and emission scenarios the concentration ratio between the downstream area and the upstream area was calculated for all compartments. From these calculations it appeared that BasinBox predicts significant concentration differences between upstream and downstream areas of the Rhine river basin for certain types of chemicals and emission scenarios. There is a clear trend of increasing chemical concentrations in downstream direction of the river basin. The calculations show that taking into account spatial variability between upstream, midstream and downstream areas of large river basins can be useful in the predictions of environmental concentrations by multimedia fate models.     

Social Relationships among Males in Multimale Siamang Groups

I quantified social and spatial interactions among adults in 4 multimale siamang (Symphalangus syndactylus) groups to evaluate the importance of aggression and avoidance in mediating male-male relationships. Actual genetic relationships among adults are unknown, but available mitochondrial data suggest that in 3 of 4 groups, neither male was the offspring or maternal sibling of the female, whereas in the fourth group, a matrilineal relationship between the female and 1 adult male was not excluded. Rates of aggression involving male-male dyads were very low. One male-female dyad maintained closer spatial cohesion than those of other adult dyads in 3 of 4 groups. Nonetheless, all adult males spent substantial percentages of their time ≤20 m from other adults in their groups. The percentages of time that male-male dyads spent in social grooming interactions did not differ from those of male-female dyads. In 3 groups, both males copulated with the group female. While previous studies have reported high rates of aggression between adult males and subadult male group members in siamangs, my results suggest that male-male relationships in multimale groups at Way Canguk were relatively harmonious. Acceptance of multimale grouping (and in some cases sexual polyandry) suggests that the benefits outweigh the costs under some circumstances. If there was a genetic relationship between males, then tolerance of delayed dispersal and copulation with the adult female may function as a form of parental investment. Males may also benefit from multimale grouping via enhanced territorial defense or reduced costs of mate defense.     

Predicting Positive and Negative Relationships in Large Social Networks

In a social network, users hold and express positive and negative attitudes (e.g. support/opposition) towards other users. Those attitudes exhibit some kind of binary relationships among the users, which play an important role in social network analysis. However, some of those binary relationships are likely to be latent as the scale of social network increases. The essence of predicting latent binary relationships have recently began to draw researchers'' attention. In this paper, we propose a machine learning algorithm for predicting positive and negative relationships in social networks inspired by structural balance theory and social status theory. More specifically, we show that when two users in the network have fewer common neighbors, the prediction accuracy of the relationship between them deteriorates. Accordingly, in the training phase, we propose a segment-based training framework to divide the training data into two subsets according to the number of common neighbors between users, and build a prediction model for each subset based on support vector machine (SVM). Moreover, to deal with large-scale social network data, we employ a sampling strategy that selects small amount of training data while maintaining high accuracy of prediction. We compare our algorithm with traditional algorithms and adaptive boosting of them. Experimental results of typical data sets show that our algorithm can deal with large social networks and consistently outperforms other methods.