984 resultados para Hamilton, Remy
Resumo:
Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising methodology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.
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Incursions of plant pests and diseases pose serious threats to food security, agricultural productivity and the natural environment. One of the challenges in confidently delimiting and eradicating incursions is how to choose from an arsenal of surveillance and quarantine approaches in order to best control multiple dispersal pathways. Anthropogenic spread (propagules carried on humans or transported on produce or equipment) can be controlled with quarantine measures, which in turn can vary in intensity. In contrast, environmental spread processes are more difficult to control, but often have a temporal signal (e.g. seasonality) which can introduce both challenges and opportunities for surveillance and control. This leads to complex decisions regarding when, where and how to search. Recent modelling investigations of surveillance performance have optimised the output of simulation models, and found that a risk-weighted randomised search can perform close to optimally. However, exactly how quarantine and surveillance strategies should change to reflect different dispersal modes remains largely unaddressed. Here we develop a spatial simulation model of a plant fungal-pathogen incursion into an agricultural region, and its subsequent surveillance and control. We include structural differences in dispersal via the interplay of biological, environmental and anthropogenic connectivity between host sites (farms). Our objective was to gain broad insights into the relative roles played by different spread modes in propagating an invasion, and how incorporating knowledge of these spread risks may improve approaches to quarantine restrictions and surveillance. We find that broad heuristic rules for quarantine restrictions fail to contain the pathogen due to residual connectivity between sites, but surveillance measures enable early detection and successfully lead to suppression of the pathogen in all farms. Alternative surveillance strategies attain similar levels of performance by incorporating environmental or anthropogenic dispersal risk in the prioritisation of sites. Our model provides the basis to develop essential insights into the effectiveness of different surveillance and quarantine decisions for fungal pathogen control. Parameterised for authentic settings it will aid our understanding of how the extent and resolution of interventions should suitably reflect the spatial structure of dispersal processes.
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Social insects such as ants, bees, wasps and termites exhibit extreme forms of altruism where some individuals remain sterile and assist other individuals in reproduction. Hamilton's inclusive fitness theory provides a powerful framework for investigating the evolution of such altruism. Using the paper wasp Ropalidia marginata, we have quantified and delineated the role of ecological, physiological, genetic and demographic factors in social evolution. An interesting feature of the models we have developed is their symmetry so that either altruism or selfishness can evolve, depending on the numerical values of various parameters. This suggests that selfish/solitary behaviour must occasionally re-emerge even from the eusocial state, It is useful to contemplate expected intermediate states during such potential reversals. We can perhaps envisage three successive steps in such a hypothetical process: i) workers revolt against the hegemony of the queen and challenge her status as the sole reproductive, ii) workers stop producing queens and one or more of them function as egg layers (functional queen/s) capable of producing both haploid as well as diploid offspring and iii) social evolution reverses completely so that a eusocial species becomes solitary, at least facultatively. It appears that the third step, namely transition from eusociality to the solitary state, is rare and has been restricted to transitions from the primitively eusocial state only. The absence of transitions from the highly eusocial state to the solitary state may be attributed to a number of 'preventing mechanisms' such as (a) queen control of workers (b) loss of spermathecae and ability to mate (c) morphological specialization (d) caste polyethism and (e) homeostasis, which must each make the transition difficult and, taken together, perhaps very difficult. However, the discovery of a transition from the highly eusocial to the solitary state can hardly he ruled out, given that little or no effort has gone into its detection. In this paper I discuss social evolution and its possible reversal and cite potential examples of stages in the transition from the social to the solitary.
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Objectives Melanoma of the skin is the third most commonly diagnosed cancer in Australia. Given the high incidence of sunburn in children and the level of sun protection provided by parents is often infrequent and/or insufficient, this research employed qualitative methodology to examine parents' beliefs about their young child's sun safe behaviour. Methods Parents (N = 21; n = 14 mothers, n = 7 fathers) of children aged 2–5 years participated in focus groups to identify commonly held beliefs about their decision to sun protect their child. Data were analysed using thematic content analysis. Results Parents generally had knowledge of the broad sun safe recommendations; however, the specific details of the recommendations were not always known. Parents reported adopting a range of sun-protective measures for their child, which depended on the time of year. A range of advantages (e.g. reducing the risk of skin cancer, developing good habits early and parental peace of mind), disadvantages (e.g. false sense of safety and preventing vitamin D absorption), barriers (e.g. child refusal) and facilitators (e.g. routine and accessibility) to performing sun safe practices were identified. Normative pressures and expectations also affected parents' motivation to be sun safe for their child. Conclusions These identified beliefs can be used to inform interventions to improve sun safe behaviours in young children who reside in a region that has the highest skin cancer incidence in the world.
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- Objectives Preschool-aged children spend substantial amounts of time engaged in screen-based activities. As parents have considerable control over their child's health behaviours during the younger years, it is important to understand those influences that guide parents' decisions about their child's screen time behaviours. - Design A prospective design with two waves of data collection, 1 week apart, was adopted. - Methods Parents (n = 207) completed a Theory of Planned Behaviour (TPB)-based questionnaire, with the addition of parental role construction (i.e., parents' expectations and beliefs of responsibility for their child's behaviour) and past behaviour. A number of underlying beliefs identified in a prior pilot study were also assessed. - Results The model explained 77% (with past behaviour accounting for 5%) of the variance in intention and 50% (with past behaviour accounting for 3%) of the variance in parental decisions to limit child screen time. Attitude, subjective norms, perceived behavioural control, parental role construction, and past behaviour predicted intentions, and intentions and past behaviour predicted follow-up behaviour. Underlying screen time beliefs (e.g., increased parental distress, pressure from friends, inconvenience) were also identified as guiding parents' decisions. - Conclusion Results support the TPB and highlight the importance of beliefs for understanding parental decisions for children's screen time behaviours, as well as the addition of parental role construction. This formative research provides necessary depth of understanding of sedentary lifestyle behaviours in young children which can be adopted in future interventions to test the efficacy of the TPB mechanisms in changing parental behaviour for their child's health.
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The aim of the study was to compare the effect physical exercise and bright light has on mood in healthy, working-age subjects with varying degrees of depressive symptoms. Previous research suggests that exercise may have beneficial effects on mood at least in subjects with depression. Bright light exposure is an effective treatment of winter depression, and possibly of non-seasonal depression as well. Limited data exist on the effect of exercise and bright light on mood in non-clinical populations, and no research has been done on the combination of these interventions. Working-age subjects were recruited through occupational health centres and 244 subjects were randomized into intervention groups: exercise, either in bright light or normal lighting, and relaxation / stretching sessions, either in bright light or normal gym lighting. During the eight-week intervention in midwinter, subjects rated their mood using a self-rating version of the Hamilton Depression Scale with additional questions for atypical depressive symptoms. The main finding of the study was that both exercise and bright-light exposure were effective in treating depressive symptoms. When the interventions were combined, the relative reduction in the Hamilton Depression Scale was 40 to 66%, and in atypical depressive symptoms even higher, 45 to 85%. Bright light exposure was more effective than exercise in treating atypical depressive symptoms. No single factor could be found that would predict a good response to these interventions. In conclusion, aerobic physical exercise twice a week during wintertime was effective in treating depressive symptoms. Adding bright light exposure to exercise increased the benefit, especially by reducing atypical depressive symptoms. Since this is so, this treatment could prevent subsequent major depressive episodes among the population generally.
Resumo:
Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.
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A detailed study is presented of the expected performance of the ATLAS detector. The reconstruction of tracks, leptons, photons, missing energy and jets is investigated, together with the performance of b-tagging and the trigger. The physics potential for a variety of interesting physics processes, within the Standard Model and beyond, is examined. The study comprises a series of notes based on simulations of the detector and physics processes, with particular emphasis given to the data expected from the first years of operation of the LHC at CERN.
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keywords: Enlightenment, Northern countries, Finland, Russia, Scotland In the 36 th edition of the almanac "Philosophical Age" published materials of international symposium «The Northern Lights - Facets of Enlightenment Culture», (held September 25-26, 2009) in The Aleksanteri Institute the University of Helsinki. Contents: Vesa Oittinen Between Radicalism and Utilitarianism — On the Profile of the Finnish Enlightenment Tatiana Artemyeva The Status of Intellectual Values in the Russian Enlightenment Oili Pulkkinen The Cosmopolitan Experience, Theoretical Histories and the Universal Science of the Scottish Enlightenment Аlla Zlatopolskaya L’autocritique des Lumières chez Rousseau et le rousseauisme russe Johannes Remy Alexander Radishchev, Ethical Consuming, and North American Quakers Kimmo Sarje Anders Chydenius and Radical Swedish Enlightenment Johan Sten Anders Johan Lexell: A Finnish Astronomer at St. Petersburg Academy of Sciences and His European Contacts Mikhail Mikeshin A Russian Adam Smith in French Style: An Example of the Transfer of Ideas Larisa Agamalian The Library of an Enlightened Russian Landowner
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We present a design of a universal gadget, consisting of two half-wave plates and two quarter-wave plates coaxially mounted, which can realize every SU (2) polarization optical transformation; to realize a given SU (2) element one simply has to rotate these plates about the common axis to angular positions characteristic of the element. The design is also geometrically interpreted in terms of Hamilton's theory of turns for the group SU (2).
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The free vibrational characteristics of a beam-column, which is having randomly varying Young's modulus and mass density and subjected to randomly distributed axial loading is analysed. The material property fluctuations and axial loadings are considered to constitute independent one-dimensional, uni-variate, homogeneous real, spatially distributed stochastic fields. Hamilton's principle is used to formulate the problem using stochastic FEM. Vibration frequencies and mode shapes are analysed for their statistical descriptions. A numerical example is shown.
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Altruism is defined as any behaviour that lowers the Darwinian fitness of the actor while increasing that of the recipient. Such altruism (especially in the form of lifetime sterility exhibited by sterile workers in eusocial insects such as ants, bees, wasps and termites) has long been considered a major difficulty for the theory of natural selection. In the 1960s W. D. Hamilton potentially solved this problem by defining a new measure of fitness that he called inclusive fitness, which also included the effect of an individual's action on the fitness of genetic relatives. This has come to be known as inclusive fitness theory, Hamilton's rule or kin selection. E. O. Wilson almost single-handedly popularized this new approach in the 1970s and thus helped create a large body of new empirical research and a large community of behavioural ecologists and kin selectionists. Adding thrill and drama to our otherwise sombre lives, Wilson is now leading a frontal attack on Hamilton's approach, claiming that the inclusive fitness theory is not as mathematically general as the standard natural selection theory, has led to no additional biological insights and should therefore be abandoned. The world cannot but sit up and take notice.
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This article documents the addition of 229 microsatellite marker loci to the Molecular Ecology Resources Database. Loci were developed for the following species: Acacia auriculiformis x Acacia mangium hybrid, Alabama argillacea, Anoplopoma fimbria, Aplochiton zebra, Brevicoryne brassicae, Bruguiera gymnorhiza, Bucorvus leadbeateri, Delphacodes detecta, Tumidagena minuta, Dictyostelium giganteum, Echinogammarus berilloni, Epimedium sagittatum, Fraxinus excelsior, Labeo chrysophekadion, Oncorhynchus clarki lewisi, Paratrechina longicornis, Phaeocystis antarctica, Pinus roxburghii and Potamilus capax. These loci were cross-tested on the following species: Acacia peregrinalis, Acacia crassicarpa, Bruguiera cylindrica, Delphacodes detecta, Tumidagena minuta, Dictyostelium macrocephalum, Dictyostelium discoideum, Dictyostelium purpureum, Dictyostelium mucoroides, Dictyostelium rosarium, Polysphondylium pallidum, Epimedium brevicornum, Epimedium koreanum, Epimedium pubescens, Epimedium wushanese and Fraxinus angustifolia.
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Competition between seeds within a fruit for parental resources is described using one-locus-two-allele models. While a �normal� allele leads to an equitable distribution of resources between seeds (a situation which also corresponds to the parental optimum), the �selfish� allele is assumed to cause the seed carrying it to usurp a higher proportion of the resources. The outcome of competition between �selfish� alleles is also assumed to lead to an asymmetric distribution of resources, the �winner� being chosen randomly. Conditions for the spread of an initially rare selfish allele and the optimal resource allocation corresponding to the evolutionarily stable strategy, derived for species with n-seeded fruits, are in accordance with expectations based on Hamilton�s inclusive fitness criteria. Competition between seeds is seen to be most intense when there are only two seeds, and decreases with increasing number of seeds, suggesting that two-seeded fruits would be rarer than one-seeded or many-seeded ones. Available data from a large number of plant species are consistent with this prediction of the model.
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An optimal control law for a general nonlinear system can be obtained by solving Hamilton-Jacobi-Bellman equation. However, it is difficult to obtain an analytical solution of this equation even for a moderately complex system. In this paper, we propose a continuoustime single network adaptive critic scheme for nonlinear control affine systems where the optimal cost-to-go function is approximated using a parametric positive semi-definite function. Unlike earlier approaches, a continuous-time weight update law is derived from the HJB equation. The stability of the system is analysed during the evolution of weights using Lyapunov theory. The effectiveness of the scheme is demonstrated through simulation examples.