13 resultados para Bees

em Queensland University of Technology - ePrints Archive


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Protection for employees from unfair dismissal (UFD) has been around in Australia under various guises for 30 years or so (Chapman, 2006). Labour standards, and particularly ILO Convention 158 (Convention Concerning Termination of Employment at the Initiative of the Employer 1982), underpin the adoption of a particular form of federal statutory UFD regime which first appeared in the 1993 reforms to the Industrial Relations Act 1998 (Commonwealth). Its existence, however, has not been uncontroversial, and the meaning, operation, scope and remedies have attracted attention over time. In fact, the first reforms to the federal UFD regime were undertaken under the Keating Labor government three months after they were enacted (Chapman, ibid.). Further reforms were made by the incoming Howard Liberal-national coalition government through the Workplace Relations Act 1996 (Commonwealth) (WRA), and arguably these reforms continued down the ‘contraction’ path (ibid.).

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We provide the first evidence for interspecific warfare in bees, a spectacular natural phenomenon that involves a series of aerial battles and leads to thousands of fatalities from both attacking and defending colonies. Molecular analysis of fights at a hive of the Australian stingless bee Tetragonula carbonaria revealed that the attack was launched by a related species, Tetragonula hockingsi, which has only recently extended its habitat into southeastern Queensland. Following a succession of attacks by the same T. hockingsi colony over a 4-month period, the defending T. carbonaria colony was defeated and the hive usurped, with the invading colony installing a new queen. We complemented our direct observations with a 5-year study of more than 260 Tetragonula hives and found interspecific hive changes, which were likely to be usurpation events, occurring in 46 hives over this period. We discuss how fighting swarms and hive usurpation fit with theoretical predictions on the evolution of fatal fighting and highlight the many unexplained features of these battles that warrant further study.

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Propolis of Australian stingless bees (Tetragonula carbonaria, Meliponini) originating from Corymbia torelliana (Myrtaceae) fruit resins was tested for its antimicrobial activities as well as its flavonoid contents. This study aimed at the isolation, structural elucidation and antibacterial testing of flavanones of C. torelliana fruit resins that are incorporated into stingless bee propolis. Flavanones of this study were elucidated by spectroscopic and spectrometric methods including UV, 1D and 2D NMR, EI-MS, ESI-MS and HR-MS. The results indicated known C-methylated flavanones namely, 1 (2S)-cryptostrobin, its regioisomer 2 (2S)- stroboponin, 3 (2S)- cryptostrobin 7-methyl ether, and 6 (2S)- desmethoxymatteucinol, and known flavanones 4 (2S)- pinostrobin and 5 (2S)- pinocembrin as markers for C. torelliana fruit resins and one propolis type. Ethanolic preparations of propolis were shown to be active against Staphylococcus aureus (ATCC 25923) and to a lesser extent against Pseudomonas aeruginosa (ATCC 27853). C. torelliana flavanones inhibited the growth of S. aureus therefore contributing to the antibacterial effects observed for Australian stingless bee propolis extracts.

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Bees are well known for being industrious pollinators. Some species, however, have taken to invading the nests of other colonies to steal food, nest material or the nest site itself. Despite the potential mortality costs due to fighting with an aggressive opponent, the prospects of a large bounty can be worth the risk. In this review, we aim to bring together current knowledge on intercolony fighting with a view to better understand the evolution of warfare in bees and identify avenues for future research. A review of literature reveals that at least 60 species of stingless bees are involved in heterospecific conflicts, either as attacking or victim colonies. The threat of invasion has led to the evolution of architectural, behavioural and morphological adaptations, such as narrow entrance tunnels, mud balls to block the entrance, decoy nests that direct invaders away from the brood chamber, fighting swarms, and soldiers that are skilled at immobilising attackers. Little is known about how victim colonies are selected, but a phylogenetically controlled analysis suggests that the notorious robber bee Lestrimelitta preferentially attacks colonies of species with more concentrated honey. Warfare among bees poses many interesting questions, including why species differ so greatly in their response to attacks and how these alternative strategies of obtaining food or new nest sites have evolved.

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The impact of urban development and climate change has created the impetus to monitor changes in the environment, particularly, the behaviour, habitat and movement of fauna species. The aim of this chapter is to present the design and development of a sensor network based on smart phones to automatically collect and analyse acoustic and visual data for environmental monitoring purposes. Due to the communication and sophisticated programming facilities offered by smart phones, software tools can be developed to allow data to be collected, partially processed and sent to a remote server over the network for storage and further processing. This sensor network which employs a client-server architecture has been deployed in three applications: monitoring a rare bird species near Brisbane Airport, study of koalas behaviour at St Bees Island, and detection of fruit flies. The users of this system include scientists (e.g. ecologists, ornithologists, computer scientists) and community groups participating in data collection or reporting on the environment (e.g. students, bird watchers). The chapter focuses on the following aspects of our research: issues involved in using smart phones as sensors; the overall framework for data acquisition, data quality control, data management and analysis; current and future applications of the smart phone-based sensor network, and our future research directions.

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Abstract. 1. Learning may enable insects to obtain nectar from flowers more efficiently. Learning in nectar foraging has been shown primarily in studies of bees and butterflies. Here, learning is demonstrated in the nectar foraging behaviour of a noctuid moth, Helicoverpa armigera. 2. The present studies show that: (1) previous experience with a flowering host species increases the probability of that species being selected for nectar foraging, and (2) previous experience of a particular flower type (food source at bottom or top of the corolla tube) increases the likelihood of the food source being found when that flower type is being searched. 3. The implications of these findings for understanding the pattern of oviposition observed in wild populations of this important pest species are discussed.

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This paper presents a new algorithm based on a Modified Particle Swarm Optimization (MPSO) to estimate the harmonic state variables in a distribution networks. The proposed algorithm performs the estimation for both amplitude and phase of each injection harmonic currents by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as the uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WTs). The main features of the proposed MPSO algorithm are usage of a primary and secondary PSO loop and applying the mutation function. The simulation results on 34-bus IEEE radial and a 70-bus realistic radial test networks are presented. The results demonstrate that the speed and the accuracy of the proposed Distribution Harmonic State Estimation (DHSE) algorithm are very excellent compared to the algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO, and Honey Bees Mating Optimization (HBMO).

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This paper presents a new algorithm based on a Hybrid Particle Swarm Optimization (PSO) and Simulated Annealing (SA) called PSO-SA to estimate harmonic state variables in distribution networks. The proposed algorithm performs estimation for both amplitude and phase of each harmonic currents injection by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WT). The main feature of proposed PSO-SA algorithm is to reach quickly around the global optimum by PSO with enabling a mutation function and then to find that optimum by SA searching algorithm. Simulation results on IEEE 34 bus radial and a realistic 70-bus radial test networks are presented to demonstrate the speed and accuracy of proposed Distribution Harmonic State Estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO and Honey Bees Mating Optimization (HBMO) algorithm.

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Honey bees are in decline, and the current method of keeping them can be disruptive to a colony. But new designs allow beekeepers to monitor a hive remotely, even sniff out disease and pests.