A simple and effective ground-based tool for sampling tree flowers at height for subsequent nectar extraction

Abstract Sampling nectar from forest canopies is logistically challenging as it requires physical access to the canopy to a height greater than that can be achieved by hand. The most common solutions comprise the use of cherry pickers, cranes or tree climbers. These techniques are generally expensive, logistically complex, and often involve additional safety risks and specialized technicians to use the equipment/machinery. In addition, access is required up to the tree for cherry pickers and cranes, and tree climbers are often unable to reach the outermost branches. Here, we propose a simple approach based on a special, easy to assemble tool, to sample tree flowers for subsequent nectar extraction, to avoid climbing and cumbersome/expensive equipment. Conducting a study on nectar production of Eucalypt trees (Myrtaceae) in southwest Australia, we conceived a practical ground‐based tool formed by an extendible pole with an adapted container at the end for covering the tree inflorescence with organza and plastic (polyethylene) bags. We experimented with the tool on dozens of trees of each of the co‐occurring species Eucalyptus marginata and Corymbia calophylla, successfully completing the following operational manoeuvres: bagging the inflorescence with an organza bag prior to the nectar collection, then bagging the inflorescence and organza bags with plastic bags if necessary, and cutting the bagged inflorescences from the branch for subsequent nectar extraction. We present the instructions for assembling the tool and we detail the sequence for bagging and sampling flowers from canopy trees, including time‐saving tips. This approach allows efficient sampling of tree flowers for subsequent nectar extraction. To effectively handle the tool while covering the inflorescence, the maximum sample collection height is approximately 10 m. Overall, the tool helps to address limitations related to sampling nectar from medium‐height trees such as costs, risks and time factors. Beyond tree flowers, the tool can be used for sampling flowers of epiphytic and climbing plants, and it could also be used to test for autogamy in flowering trees

The Right to the Sustainable Smart City

Environmental concerns have driven an interest in sustainable smart cities, through the monitoring and optimisation of networked infrastructures. At the same time, there are concerns about who these interventions and services are for, and who benefits. HCI researchers and designers interested in civic life have started to call for the democratisation of urban space through resistance and political action to challenge state and corporate claims. This paper contributes to an emerging body of work that seeks to involve citizens in the design of sustainable smart cities, particularly in the context of marginalised and culturally diverse urban communities. We present a study involving co- designing Internet of Things with urban agricultural communities and discuss three ways in which design can participate in the right to the sustainable smart city through designing for the commons, care, and biocultural diversity

Machine learning regression model for predicting honey harvests

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Honey yield from apiary sites varies significantly between years. This affects the beekeeper’s ability to manage hive health, as well as honey production. This also has implications for ecosystem services, such as forage availability for nectarivores or seed sets. This study investigates whether machine learning methods can develop predictive harvest models of a key nectar source for honeybees, Corymbia calophylla (marri) trees from South West Australia, using data from weather stations and remotely sensed datasets. Honey harvest data, weather and vegetation-related datasets from satellite sensors were input features for machine learning algorithms. Regression trees were able to predict the marri honey harvested per hive to a Mean Average Error (MAE) of 10.3 kg. Reducing input features based on their relative model importance achieved a MAE of 11.7 kg using the November temperature as the sole input feature, two months before marri trees typically start to produce nectar. Combining weather and satellite data and machine learning has delivered a model that quantitatively predicts harvest potential per hive. This can be used by beekeepers to adaptively manage their apiary. This approach may be readily applied to other regions or forage species, or used for the assessment of some ecosystem services

A Comparison of the Interiors of Jupiter and Saturn

Interior models of Jupiter and Saturn are calculated and compared in the framework of the three-layer assumption, which rely on the perception that both planets consist of three globally homogeneous regions: a dense core, a metallic hydrogen envelope, and a molecular hydrogen envelope. Within this framework, constraints on the core mass and abundance of heavy elements (i.e. elements other than hydrogen and helium) are given by accounting for uncertainties on the measured gravitational moments, surface temperature, surface helium abundance, and on the inferred protosolar helium abundance, equations of state, temperature profile and solid/differential interior rotation.Comment: 25 pages, 6 tables, 10 figures Planetary and Space Science, in pres

Methicillin-Susceptible Staphylococcus aureus in Skin and Soft Tissue Infections, Northern Italy

Summary statement: A community outbreak with intrafamilial skin infections was associated with an MSSA clone

The feasibility of using pattern recognition software to measure the influence of computer use on the consultation

BACKGROUND: A key feature of a good general practice consultation is that it is patient-centred. A number of verbal and non-verbal behaviours have been identified as important to establish a good relationship with the patient. However, the use of the computer detracts the doctor's attention away from the patient, compromising these essential elements of the consultation. Current methods to assess the consultation and the influence of the computer on them are time consuming and subjective. If it were possible to measure these quantitatively, it could provide the basis for the first truly objective way of studying the influence of the computer on the consultation. The aim was to assess whether pattern recognition software could be used to measure the influence and pattern of computer use in the consultation. If this proved possible it would provide, for the first time, an objective quantitative measure of computer use and a measure of the attention and responsiveness of the general practitioner towards the patient. METHODS: A feasibility study using pattern recognition software to analyse a consultation was conducted. A web camera, linked to a data-gathering node was used to film a simulated consultation in a standard office. Members of the research team enacted the role of the doctor and the patient, using pattern recognition software to try and capture patient-centred, non-verbal behaviour. As this was a feasibility study detailed results of the analysis are not presented. RESULTS: It was revealed that pattern recognition software could be used to analyse certain aspects of a simulated consultation. For example, trigger lines enabled the number of times the clinician's hand covered the keyboard to be counted and wrapping recorded the number of times the clinician nodded his head. It was also possible to measure time sequences and whether the movement was brief or lingering. CONCLUSION: Pattern recognition software enables movements associated with patient-centredness to be recorded. Pattern recognition software has the potential to provide an objective, quantitative measure of the influence of the computer on the consultation

Review on Superconducting Materials

Short review of the topical comprehension of the superconductor materials classes Cuprate High-Temperature Superconductors, other oxide superconductors, Iron-based Superconductors, Heavy-Fermion Superconductors, Nitride Superconductors, Organic and other Carbon-based Superconductors and Boride and Borocarbide Superconductors, featuring their present theoretical understanding and their aspects with respect to technical applications.Comment: A previous version of this article has been published in \" Applied Superconductivity: Handbook on Devices and Applications \", Wiley-VCH ISBN: 978-3-527-41209-9. The new extended and updated version will be published in \" Encyclopedia of Applied Physics \", Wiley-VC

Population Structure of Staphylococcus aureus from Remote African Babongo Pygmies

Staphylococcus aureus is a bacterium that colonizes humans worldwide. The anterior nares are its main ecological niche. Carriers of S. aureus are at a higher risk of developing invasive infections. Few reports indicated a different clonal structure and profile of virulence factors in S. aureus isolates from Sub-Saharan Africa. As there are no data about isolates from remote indigenous African populations, we conducted a cross-sectional survey of S. aureus nasal carriage in Gabonese Babongo Pygmies. The isolates were characterized regarding their susceptibility to antibiotic agents, possession of virulence factors and clonal lineage. While similar carriage rates were found in populations of industrialized countries, isolates that encode the genes for the Panton-Valentine leukocidin (PVL) were clearly more prevalent than in European countries. Of interest, many methicillin-susceptible S. aureus isolates from Babongo Pygmies showed the same genetic background as pandemic methicillin-resistant S. aureus (MRSA) clones. We advocate a surveillance of S. aureus in neglected African populations to control the development of resistance to antibiotic drugs with particular respect to MRSA and to assess the impact of the high prevalence of PVL-positive isolates