Multiple mating and a low incidence of cuckoldry for nest-holding males in the two-spotted goby, Gobiusculus flavescens

Background: A major question in behavioural ecology concerns the relationship between genetic mating systems and the strength of sexual selection. In this study, we investigated the genetic mating system of the two-spotted goby (Gobiusculus flavescens), a useful fish model for the study of sexual selection whose genetic mating system remains uncharacterized. We developed four polymorphic microsatellite markers and used them to conduct parentage analyses on 21 nests collected during the breeding season to examine the rates of multiple mating by males and to test for evidence of alternative mating strategies.

Results: Results of this study indicate that male G. flavescens mate with multiple females and enjoy confidence of paternity. We detected only one instance of sneaking, so cuckoldry contributed a very small percentage (~0.1%) of the total fertilizations in this population. Nests were nearly full and males that maintain larger nests have higher mating and reproductive success, irrespective of body size.

Conclusion: Overall, our investigation shows that G. flavescens is similar to other, related gobies in that the nests of care-giving males often contain eggs from multiple females. However, G. flavescens differs from other gobies in displaying an extremely low rate of cuckoldry. The study of ecological factors responsible for this important

Activity preferences and participation of school-age children living in urban and rural environments

It is important for therapists to be knowledgeable about the impact of the environment on children’s participation patterns and activity preferences. This study investigated the activity preference and participation among school-age children living in urban and rural locations. The participation patterns and preferences for activities of 58 typically developing children (32 males and 26 females; response rate of 38.7%) aged 8–12 years were assessed across both urban (n = 24) and rural (n = 34) regions of southwest Victoria, Australia. The participation patterns and preferences for activities were assessed using the Children’s Assessment of Participation and Enjoyment and Preferences for Activities of Children (CAPE/PAC).An independent samples t-test was used to determinewhether significant differences existed for theCAPE/PACscores for urban and rurally based children as well as boys and girls. Significant differences were found between the scores of children living in urban and rural areas on the following subscales: CAPE Diversity, CAPE Intensity, CAPE Whom, CAPE Where, PAC Physical Preference, and PACSocial Preference.Asignificant difference for rural and urban groups was found on the following CAPE activity types:Recreation Diversity,Recreation Intensity, Social Diversity, Social Intensity, Self-Improvement Diversity, and Self-Improvement Intensity. Rurally based children were engaged in a broader range of activities and did so more frequently than urban children. Differences in gender were identified with girls preferring to participate in social and skill-based activities and being more likely to participate with friends or people outside their home. However, there were no significant differences in the participation patterns of boys and girls. Physical, social, and structural aspects of the location where a child lives impact the frequency, type of activities, and whom a child participates with most frequently in out-of-school activities. The activity participation of boys and girls in Australia has become quite similar.

Website physical activity interventions : preferences of potential users

Information and communication technologies (particularly websites and e-mail) have the potential to deliver health behavior change programs to large numbers of adults at low cost. Controlled trials using these new media to promote physical activity have produced mixed results. User-centered development methods can assist in understanding the preferences of potential participants for website functions and content, and may lead to more effective programs. Eight focus group discussions were conducted with 40 adults after they had accessed a previously trialed physical activity website. The discussions were audio taped, transcribed and interpreted using a themed analysis method. Four key themes emerged: structure, interactivity, environmental context and content. Preferences were expressed for websites that include simple interactive features, together with information on local community activity opportunities. Particular suggestions included online community notice boards, personalized progress charts, e-mail access to expert advice and access to information on specific local physical activity facilities and services. Website physical activity interventions could usefully include personally relevant interactive and environmentally focused features and services identified through a user-centered development process.

Learning other agents' preferences in multi-agent negotiation using the bayesian classifier

In multi-agent systems, most of the time, an agent does not have complete information about the preferences and decision making processes of other agents. This prevents even the cooperative agents from making coordinated choices, purely due to their ignorance of what others want. To overcome this problem, traditional coordination methods rely heavily on inter-agent communication, and thus become very inefficient when communication is costly or simply not desirable (e.g. to preserve privacy). In this paper, we propose the use of learning to complement communication in acquiring knowledge about other agents. We augment the communication-intensive negotiating agent architecture with a learning module, implemented as a Bayesian classifier. This allows our agents to incrementally update models of other agents' preferences from past negotiations with them. Based on these models, the agents can make sound predictions about others' preferences, thus reducing the need for communication in their future interactions.

Learning other agents' preferences in multiagent negotiation

In multiagent systems, an agent does not usually have complete information about the preferences and decision making processes of other agents. This might prevent the agents from making coordinated choices, purely due to their ignorance of what others want. This paper describes the integration of a learning module into a communication-intensive negotiating agent architecture. The learning module gives the agents the ability to learn about other agents' preferences via past interactions. Over time, the agents can incrementally update their models of other agents' preferences and use them to make better coordinated decisions. Combining both communication and learning, as two complement knowledge acquisition methods, helps to reduce the amount of communication needed on average, and is justified in situations where communication is computationally costly or simply not desirable (e.g. to preserve the individual privacy).

Negotiating agents that learn about others’ preferences

In multiagent systems, an agent does not usually have complete information about the preferences and decision making processes of other agents. This might prevent the agents from making coordinated choices, purely due to their ignorance of what others want. This paper describes the integration of a learning module into a communication-intensive negotiating agent architecture. The learning module gives the agents the ability to learn about other agents’ preferences via past interactions. Over time, the agents can incrementally update their models of other agents’ preferences and use them to make better coordinated decisions. Combining both communication and learning, as two complement knowledge acquisition methods, helps to reduce the amount of communication needed on average, and is justified in situation where communication is computationally costly or simply not desirable (e.g. to preserve the individual privacy).

Aggregation of preferences in recommender systems

This chapter gives an overview of aggregation functions toward their use in recommender systems. Simple aggregation functions such as the arithmetic mean are often employed to aggregate user features, item ratings, measures of similarity, etc., however many other aggregation functions exist which could deliver increased accuracy and flexibility to many systems. We provide definitions of some important families and properties, sophisticated methods of construction, and various examples of aggregation functions in the domain of recommender systems.

Language and learning preferences : a study of university students in Australia

This study sought to investigate the preferences for language use and modes of learning of university students who were completing undergraduate degrees in Australia. Of the sixty students surveyed, forty percent were international students. For seventy five percent of all students sampled, either they or their parents (or both) were bi- or multilingual. Questions which this research sought to answer were: Do the preferences for learning of university students differ according to the culture and / or language backgrounds of the students? Does an individual student’s preferred learning style influence the student’s preferences for learning in a group situation? For students whose first language is not English, do their preferences for language use vary in group learning? General findings resulting from a statistical analysis of responses to the questionnaire indicated in many, but not all, cases that the preferences for learning of university students differed according to the cultural and / or language backgrounds of the students, that an individual student’s preferred learning style influenced the student’s preferences for learning in a group situation, and that the preferences for language use of students whose first language was not English varied in group learning. Reid’s (1984 in Richards, J.C. & Lockhart, C., 1994) “Perceptual learning style preference questionnaire” comprised one section of the questionnaire for this study. This replication made possible a comparison of the findings which related to students’ learning styles from this study with findings from similar studies in which Reid’s survey instrument had been used. Findings of the present study indicate a number of differences from Reid’s findings. This study found, for example, that most language groups showed a minor preference for group learning using this survey instrument whereas Reid had found that group learning was a negligible preference for most of the language groups in her study. This study may give tertiary educators a greater understanding of their students’ preferences for group and other learning styles. It may also inform them of the likely preferences for language use of those of their students who have first languages other than English. Future students may benefit from this.

Response to comment on "Illusions promote mating success in great bowerbirds"

Borgia et al. raise some questions about our recent study showing that great bowerbirds create visual illusions that are used in mate choice. We address them by providing further details about our methods and results. We also provide detailed descriptions of our geometric calculations to address their measurement and analysis questions.

Illusions promote mating success in great bowerbirds

Sexual selection studies normally compare signal strengths, but signal components and sensory processing may interact to create misleading or attention-capturing illusions. Visual illusions can be produced by altering object and scene geometry in ways that trick the viewer when seen from a particular direction. Male great bowerbirds actively maintain size-distance gradients of objects on their bower courts that create forced-perspective illusions for females viewing their displays from within the bower avenue. We show a significant relationship between mating success and the female's view of the gradient; this view explains substantially more variance in mating success than the strength of the gradients. Illusions may be widespread in other animals because males of most species display to females with characteristic orientation and distance, providing excellent conditions for illusions.

Females use multiple mating and genetically loaded sperm competition to target compatible genes

Individuals in socially monogamous species may participate in copulations outside of the pair bond, resulting in extra-pair offspring. Although males benefit from such extra-pair behavior if they produce more offspring, the adaptive function of infidelity to females remains elusive. Here we show that female participation in extra-pair copulations, combined with a genetically loaded process of sperm competition, enables female finches to target genes that are optimally compatible with their own to ensure fertility and optimize offspring viability. Such female behavior, along with the postcopulatory processes demonstrated here, may provide an adaptive function of female infidelity in socially monogamous animals.

An effective semi-supervised clustering framework integrating pairwise constraints and attribute preferences

Both the instance level knowledge and the attribute level knowledge can improve clustering quality, but how to effectively utilize both of them is an essential problem to solve. This paper proposes a wrapper framework for semi-supervised clustering, which aims to gracely integrate both kinds of priori knowledge in the clustering process, the instance level knowledge in the form of pairwise constraints and the attribute level knowledge in the form of attribute order preferences. The wrapped algorithm is then designed as a semi-supervised clustering process which transforms this clustering problem into an optimization problem. The experimental results demonstrate the effectiveness and potential of proposed method.

A fuzzy decision support method for customer preferences analysis based on Choquet integral

The explosion of the Web 2:0 platforms, with massive volume of user generated data, has presented many new opportunities as well as challenges for organizations in understanding consumer's behavior to support for business planning process. Feature based sentiment mining has been an emerging area in providing tools for automated opinion discovery and summarization to help business managers with achieving such goals. However, the current feature based sentiment mining systems were only able to provide some forms of sentiments summary with respect to product features, but impossible to provide insight into the decision making process of consumers. In this paper, we will present a relatively new decision support method based on Choquet Integral aggregation function, Shapley value and Interaction Index which is able to address such requirements of business managers. Using a study case of Hotel industry, we will demonstrate how this technique can be applied to effectively model the user's preference of (hotel) features. The presented method has potential to extend the practical capability of sentiment mining area, while, research findings and analysis are useful in helping business managers to define new target customers and to plan more effective marketing strategies.