999 research outputs found
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Cassava brown streak virus disease: Past, present and future.
Cassava has been an important success story in Africa's developing agriculture over the past decade. The crop's inherei'lt capacity to cope with marginal growing conditions and unpredictable rainfall, coupled with determined efforts of a number of countries to move away from over-reliance on maize, have helped establish it as the continent's number one crop in terms of total fresh production. The hope provided by these gains is now threatened, however, by the devastating impact of the virus diseases, cassava mosaic and cassava brown streak. Both have been known for many years, but seem to be becoming increasingly damaging, and pose an ever greater threat to the livelihoods of the millions of Africans who depend on cassava as a food staple. Substantial effort has been directed towards understanding and managing cassava mosaic. By contrast, cassava brown streak disease (CBSD), which has a more limited distribution, and causes most severe damage in the coastal lowlands of Eastern and Southern Africa, has received little attention. In order to address this deficiency, an international workshop was convened at Mombasa, Kenya. This meeting brought together a diverse range of cassava stakeholders with the twin aims of reviewing current research into cassava brown streak and developing a plan to guide future research for development initiatives. The IS papers presented in these proceedings provide a useful and informative summary of the history and current status of CBSD, recent research initiatives and management options for the worst affected countries - Malawi, Tanzania, Kenya and Mozambique. Outputs of the research and on-farm working group sessions are also included. lt is anticipated that this information will serve both as a useful technical resource as well as an essential planning tool for scientists, development workers and others with an interest in the management of CBSD and the development of cassava in Africa
Improving accuracy and efficiency of mutual information for multi-modal retinal image registration using adaptive probability density estimation
Mutual information (MI) is a popular similarity measure for performing image registration between different modalities. MI makes a statistical comparison between two images by computing the entropy from the probability distribution of the data. Therefore, to obtain an accurate registration it is important to have an accurate estimation of the true underlying probability distribution. Within the statistics literature, many methods have been proposed for finding the 'optimal' probability density, with the aim of improving the estimation by means of optimal histogram bin size selection. This provokes the common question of how many bins should actually be used when constructing a histogram. There is no definitive answer to this. This question itself has received little attention in the MI literature, and yet this issue is critical to the effectiveness of the algorithm. The purpose of this paper is to highlight this fundamental element of the MI algorithm. We present a comprehensive study that introduces methods from statistics literature and incorporates these for image registration. We demonstrate this work for registration of multi-modal retinal images: colour fundus photographs and scanning laser ophthalmoscope images. The registration of these modalities offers significant enhancement to early glaucoma detection, however traditional registration techniques fail to perform sufficiently well. We find that adaptive probability density estimation heavily impacts on registration accuracy and runtime, improving over traditional binning techniques. © 2013 Elsevier Ltd
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The effect of competition on the control of invading plant pathogens
1. New invading pathogen strains must compete with endemic pathogen strains to emerge and spread. As disease control measures are often non-specific, i.e. they do not distinguish between strains, applying control not only affects the invading pathogen strain but the endemic as well. We hypothesise that the control of the invasive strain could be compromised due to the non-specific nature of the control.
2. A spatially-explicit model, describing the East African cassava mosaic virus-Uganda strain (EACMV-UG) outbreak, is used to evaluate methods of controlling both disease incidence and spread of invading pathogen strains in pathosystems with and without an endemic pathogen strain present.
3. We find that while many newly introduced or intensified control measures (such as resistant cultivars or roguing) decrease the expected incidence, they have the unintended consequence of increasing, or at least not reducing, the speed with which the invasive pathogen spreads geographically. We identify which controls cause this effect and methods in which these controls may be applied to prevent it.
4. We found that the spatial spread of the invading strain is chiefly governed by the incidence at the wave front. Control can therefore be applied, or intensified, once the wave front has passed without increasing the pathogenâs rate of spread.
5. When trade of planting material occurs, it is possible that the planting material is already infected. The only forms of control in this study that reduces the speed of geographic spread, regardless of the presence of an endemic strain, are those that reduce the amount of trade and the distance over which trade takes place.
6. Synthesis and applications. Imposing trade restrictions before the epidemic has reached a given area and increasing other control methods only once the wave front has passed is the most effective way of both slowing down spread and controlling incidence when the presence of an endemic strain is unknow
Challenges associated with x-ray imaging of stretcher-bound patients
Patients often arrive at imaging departments on stretchers, and in certain circumstances they must remain on the stretcher for the imaging examination to reduce the likelihood of exacerbating injuries. Imaging stretcher-bound patients can be challenging, with many physical and technical variables to consider. These challenges occur because of differences between imaging a patient on a tabletop and imaging a patient on a stretcher. This article reviews the issues associated with imaging stretcher-
bound patients, including the unavailability of the automatic exposure control, different grids used, geometric factors, and variability in stretcher design
International legislation on white slavery and anti-trafficking in the early 20th century
The chapter focuses on the emergence of international legislation against trafficking in the early twentieth century, focusing on the years between 1904 and 1949. The chapter will introduce key legal measures adopted during that time but focus on the enactment of the International Agreement for the Suppression of the âWhite Slave Trafficâ 1904 and the International Convention for the Suppression of the White Slave Traffic 1910. These measures, unlike modern anti-trafficking legal standards that recognize more comprehensive forms of exploitation, focused solely on recruitment for prostitution and the exploitation of prostitution. The chapter argues that the early-twentieth-century legal framework was mostly a result of civil society action in the field and that the framework enabled the control of immigration and emigration of young women. The chapter will further show how the terminology changed from âwhite slaveryâ to a more neutral âtrafficâ with the League of Nations. Despite this change, immigration control and nationalism continued to underline much of the rhetoric even after the League of Nations took over the legal framework in 1921
Superconductivity in an Einstein Solid AxV2Al20 (A = Al and Ga)
A cage compound AxV2Al20 (Al10V), that was called an Einstein solid by Caplin
and coworkers 40 years ago, is revisited to investigate the low-energy, local
vibrations of the A atoms and their influence on the electronic and
superconducting properties of the compound. Polycrystalline samples with A =
Al, Ga, Y, and La are studied through resistivity and heat capacity
measurements. Weak-coupling BCS superconductivity is observed below Tc = 1.49,
1.66, and 0.69 K for Ax = Al0.3, Ga0.2, and Y, respectively, but not above 0.4
K for Ax = La. Low-energy modes are detected only for A = Al and Ga, which are
approximately described by the Einstein model with Einstein temperatures of 24
and 8 K, respectively. A weak but significant coupling between the low-energy
modes, which are almost identical to those called rattling in recent study, and
conduction electrons manifests itself as anomalous enhancement in resistivity
at around low temperatures corresponding to the Einstein temperatures.Comment: 12 pages, 5 figures, to be published in J. Phys. Soc. Jp
Spatial Analysis of Temporal Changes in the Pandemic of Severe Cassava Mosaic Disease in Northwestern Tanzania
Published online: 8 Sept 2017To improve understanding of the dynamics of the cassava mosaic disease (CMD) pandemic front, geospatial approaches were applied to the analysis of 3 yearsâ data obtained from a 2-by-2° (approximately 222-by-222 km) area of northwestern Tanzania. In total, 80 farmersâ fields were assessed in each of 2009, 2010, and 2011, with 20 evenly distributed fields per 1-by-1° quadrant. CMD-associated variables (CMD incidence, CMD severity, vector-borne CMD infection, and vector abundance) increased in magnitude from 2009 to 2010 but showed little change from 2010 to 2011. Increases occurred primarily in the two westernmost quadrants of the study area. A pandemic âfrontâ was defined by determining the values of CMD incidence and whitefly abundance where predicted disease gradients were greatest. The pandemic-associated virus (East African cassava mosaic virus-Uganda) and vector genotype (Bemisia tabaci sub-Saharan Africa 1âsubgroup 1) were both present within the area bounded by the CMD incidence front but both also occurred ahead of the front. The average speed and direction of movement of the CMD incidence front (22.9 km/year; southeast) and whitefly abundance front (46.6 km/year; southeast) were calculated, and production losses due to CMD were estimated to range from US$4.3 million to 12.2 million
Acceptability, Precision and Accuracy of 3D Photonic Scanning for Measurement of Body Shape in a Multi-Ethnic Sample of Children Aged 5-11 Years: The SLIC Study.
Information on body size and shape is used to interpret many aspects of physiology, including nutritional status, cardio-metabolic risk and lung function. Such data have traditionally been obtained through manual anthropometry, which becomes time-consuming when many measurements are required. 3D photonic scanning (3D-PS) of body surface topography represents an alternative digital technique, previously applied successfully in large studies of adults. The acceptability, precision and accuracy of 3D-PS in young children have not been assessed
Visual analytics for collaborative human-machine confidence in human-centric active learning tasks
Active machine learning is a human-centric paradigm that leverages a small labelled dataset to build an initial weak classifier, that can then be improved over time through human-machine collaboration. As new unlabelled samples are observed, the machine can either provide a prediction, or query a human âoracleâ when the machine is not confident in its prediction. Of course, just as the machine may lack confidence, the same can also be true of a human âoracleâ: humans are not all-knowing, untiring oracles. A humanâs ability to provide an accurate and confident response will often vary between queries, according to the duration of the current interaction, their level of engagement with the system, and the difficulty of the labelling task. This poses an important question of how uncertainty can be expressed and accounted for in a human-machine collaboration. In short, how can we facilitate a mutually-transparent collaboration between two uncertain actors - a person and a machine - that leads to an improved outcome?In this work, we demonstrate the benefit of human-machine collaboration within the process of active learning, where limited data samples are available or where labelling costs are high. To achieve this, we developed a visual analytics tool for active learning that promotes transparency, inspection, understanding and trust, of the learning process through human-machine collaboration. Fundamental to the notion of confidence, both parties can report their level of confidence during active learning tasks using the tool, such that this can be used to inform learning. Human confidence of labels can be accounted for by the machine, the machine can query for samples based on confidence measures, and the machine can report confidence of current predictions to the human, to further the trust and transparency between the collaborative parties. In particular, we find that this can improve the robustness of the classifier when incorrect sample labels are provided, due to unconfidence or fatigue. Reported confidences can also better inform human-machine sample selection in collaborative sampling. Our experimentation compares the impact of different selection strategies for acquiring samples: machine-driven, human-driven, and collaborative selection. We demonstrate how a collaborative approach can improve trust in the model robustness, achieving high accuracy and low user correction, with only limited data sample selections
Cassava whitefly, Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae), in sub-Saharan African farming landscapes: a review of the factors determining abundance
Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) is a pest species complex that causes widespread damage to cassava, a staple food crop for millions of smallholder households in Sub-Saharan Africa. Species in the complex cause direct feeding damage to cassava and are the vectors of multiple plant viruses. Whilst significant work has gone into developing virus-resistant cassava cultivars, there has been little research effort aimed at understanding the ecology of these insect vectors. In this review we critically assess the knowledge base relating to factors that may lead to high population densities of Sub-Saharan African (SSA) Bemisia tabaci species in cassava production landscapes of East Africa. We focus first on empirical studies that have examined biotic or abiotic factors that may lead to high populations. We then identify knowledge gaps that need to be filled to deliver long-term sustainable solutions to manage both the vectors and the viruses that they transmit. We found that whilst many hypotheses have been put forward to explain the increases in abundance witnessed since the early 1990s, there are little available published data and these tend to have been collected in a piecemeal manner. The most critical knowledge gaps identified were: (i) understanding how cassava cultivars and alternative host plants impact B. tabaci population dynamics and its natural enemies; (ii) the impact of natural enemies in terms of reducing the frequency of outbreaks and (iii) the use and management of insecticides to delay or avoid the development of resistance. In addition, there are several fundamental methodologies that need to be developed and deployed in East Africa to address some of the more challenging knowledge gaps
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