Paternity frequency and maternity of males in some stingless bee species

In monogynous hymenopteran societies, the number of mates of a queen strongly influences the potential for conflict between workers and queens over the maternity of males. Queens always 'prefer' their own sons to sons of workers, regardless of queen mating frequency. When a queen mates once, workers are more closely related to, and therefore are expected to prefer, their own sons and then sons of sisters to sons of the queen. However, if effective paternity frequency exceeds 2, workers on average should prefer queen-produced males to males produced by their sisters. We studied the queen mating frequency of seven stingless bee species: the Mexican species Scaptotrigona mexicana , S. pectoralis and the Australian species Austroplebeia symei , Trigona clypearis , T. hockingsi , T. mellipes and T. sapiens . We then determined whether males arise from eggs laid by workers or queens in A. symei , T. clypearis , T. hockingsi and T. mellipes . We show that all seven species investigated are most likely singly mated and that the queen dominates reproduction. This indicates that the queen's mating frequency alone does not determine whether workers or the queen produces the males.

Early birds are sexy: male age, dawn song and extrapair paternity in blue tits, Cyanistes (formerly Parus) caeruleus

Sexual selection theory predicts that signals reflecting the relative quality of individuals should be used in mate choice. Females could base their choice of copulation partners on male secondary sexual traits that honestly signal male age, as predicted by the age-based indicator mechanism. Studies have shown that female blue tits prefer older males and that aspects of dawn song reflect male quality, but it remains unknown whether dawn song characteristics correlate with male age. We compared dawn song characteristics of second-year (SY) and older (ASY) male blue tits (cross-sectional analysis), and tested for age-related changes within individuals (longitudinal analysis) and differential overwinter survival of SY males. We further investigated the relation between dawn song and paternity gain and loss. We found that ASY male blue tits began to sing earlier relative to sunrise than did SY males. This difference in the onset of dawn singing was due to age-related changes in individual performance rather than differential survival of individuals with varying expression of the trait. Males that began to sing earlier at dawn had more mating partners, and were more likely to gain extrapair paternity. Our findings suggest that the onset of dawn song can provide a simple mechanism for females to assess the relative quality of their mate and of neighbouring males. We propose that females use the onset of singing as a cue for their choice of extrapair partners. (c) 2006 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

A Context-Dependent Algorithm for Merging Uncertain Information in Possibility Theory

The need to merge multiple sources of uncertaininformation is an important issue in many application areas,especially when there is potential for contradictions betweensources. Possibility theory offers a flexible framework to represent,and reason with, uncertain information, and there isa range of merging operators, such as the conjunctive anddisjunctive operators, for combining information. However, withthe proposals to date, the context of the information to be mergedis largely ignored during the process of selecting which mergingoperators to use. To address this shortcoming, in this paper,we propose an adaptive merging algorithm which selects largelypartially maximal consistent subsets (LPMCSs) of sources, thatcan be merged through relaxation of the conjunctive operator, byassessing the coherence of the information in each subset. In thisway, a fusion process can integrate both conjunctive and disjunctiveoperators in a more flexible manner and thereby be morecontext dependent. A comparison with related merging methodsshows how our algorithm can produce a more consensual result.

A framework for managing uncertain inputs: An axiomization of rewarding

The success postulate in belief revision ensures that new evidence (input) is always trusted. However, admitting uncertain input has been questioned by many researchers. Darwiche and Pearl argued that strengths of evidence should be introduced to determine the outcome of belief change, and provided a preliminary definition towards this thought. In this paper, we start with Darwiche and Pearl’s idea aiming to develop a framework that can capture the influence of the strengths of inputs with some rational assumptions. To achieve this, we first define epistemic states to represent beliefs attached with strength, and then present a set of postulates to describe the change process on epistemic states that is determined by the strengths of input and establish representation theorems to characterize these postulates. As a result, we obtain a unique rewarding operator which is proved to be a merging operator that is in line with many other works. We also investigate existing postulates on belief merging and compare them with our postulates. In addition, we show that from an epistemic state, a corresponding ordinal conditional function by Spohn can be derived and the result of combining two epistemic states is thus reduced to the result of combining two corresponding ordinal conditional functions proposed by Laverny and Lang. Furthermore, when reduced to the belief revision situation, we prove that our results induce all the Darwiche and Pearl’s postulates as well as the Recalcitrance postulate and the Independence postulate.

Dynamic pricing models for used products in remanufacturing with lost-sales and uncertain quality

In this paper, we investigate the remanufacturing problem of pricing single-class used products (cores) in the face of random price-dependent returns and random demand. Specifically, we propose a dynamic pricing policy for the cores and then model the problem as a continuous-time Markov decision process. Our models are designed to address three objectives: finite horizon total cost minimization, infinite horizon discounted cost, and average cost minimization. Besides proving optimal policy uniqueness and establishing monotonicity results for the infinite horizon problem, we also characterize the structures of the optimal policies, which can greatly simplify the computational procedure. Finally, we use computational examples to assess the impacts of specific parameters on optimal price and reveal the benefits of a dynamic pricing policy. © 2013 Elsevier B.V. All rights reserved.

Extreme events and the morphodynamics of gravel-dominated coastal barriers: Strengthening uncertain ground

The long-term morphodynamic ordering of gravel-dominated coastal systems (GDCS), many of which serve as coastal defences in northwest Europe, is dominated by extreme events that generate barrier crest overflow. An understanding of this morphodynamic ordering is fraught with several unresolved difficulties. These are related to the twin problems of the inadequacy of pertinent morphodynamic parameterisation and of obtaining data from modern shores enabling such parameterisation. Major uncertainties concern the timing of over-crest flow in terms of return period of extreme elevation; the intensity and structure of the overflow field; antecedent beachface characteristics in response to storms; the rate of relative sea-level change; tidal stage control; and barrier resistance to forcing, itself determined by a number of unknowns including barrier form and size, sediment size and mosaics, and barrier resilience. While generalised extreme value modelling may provide a means of characterising overwashing return-period and its variability, exceptional tsunami events are outside the scope of such modelling. The characterisation of GDCS morphodynamics in terms of the forcing extreme events will necessitate integrating some or all of these parameters into a single model.

Review: M. Everson and E. Vos (eds.), Uncertain Risks Regulated (Routledge-Cavendish, 2009)

Review of edited collection.

Adaptive uncertain information fusion to enhance plan selection in BDI agent systems

Correctly modelling and reasoning with uncertain information from heterogeneous sources in large-scale systems is critical when the reliability is unknown and we still want to derive adequate conclusions. To this end, context-dependent merging strategies have been proposed in the literature. In this paper we investigate how one such context-dependent merging strategy (originally defined for possibility theory), called largely partially maximal consistent subsets (LPMCS), can be adapted to Dempster-Shafer (DS) theory. We identify those measures for the degree of uncertainty and internal conflict that are available in DS theory and show how they can be used for guiding LPMCS merging. A simplified real-world power distribution scenario illustrates our framework. We also briefly discuss how our approach can be incorporated into a multi-agent programming language, thus leading to better plan selection and decision making.