Broad Bean Mottle Virus: Identification, Serology, Host Range, and Occurrence on Faba Bean (Vicia Faba) in West Asia and Norm Africa

One of the faba bean viruses found in West Asia and North Africa was identified as broad bean mottle virus (BBMV) by host reactions, particle morphology and size, serology, and granular, often vesiculated cytoplasmic inclusions. Detailed research on four isolates, one each from Morocco, Tunisia, Sudan and Syria, provided new information on the virus. The isolates, though indistinguishable in ELISA or gel-diffusion tests, differed slightly in host range and symptoms. Twenty-one species (12 legumes and 9 non-legumes) out of 27 tested were systemically infected, and 14 of these by all four isolates. Infection in several species was symptomless, but major legumes such as chickpea, lentil and especially pea, suffered severely from infection. All 23 genotypes of faba bean, 2 of chickpea, 4 of lentil, 11 out of 21 of Phaseolus bean, and 16 out of 17 of pea were systemically sensitive to the virus. Twelve plant species were found to be new potential hosts and cucumber a new local-lesion test plant of the virus. BBMV particles occurred in faba bean plants in very high concentrations and seed transmission in this species (1.37%) was confirmed. An isolate from Syria was purified and two antisera were produced, one of which was used in ELISA to detect BBMV in faba bean field samples. Two hundred and three out of the 789 samples with symptoms suggestive of virus infection collected in 1985, 1986 and 1987, were found infected with BBMV: 4 out of 70 (4/70) tested samples from Egypt, 0/44 from Lebanon, 1/15 from Morocco, 46/254 from Sudan, 72/269 from Syria and 80/137 from Tunisia. This is the first report on its occurrence in Egypt, Syria and Tunisia. The virus is a potential threat to crop improvement in the region.

New insights into Crustal Contributions to Large-volume Rhyolite Generation in the Mid-Tertiary Sierra Madre Occidental Province, Mexico, revealed by U Pb Geochronology

Voluminous (≥3·9 × 105 km3), prolonged (∼18 Myr) explosive silicic volcanism makes the mid-Tertiary Sierra Madre Occidental province of Mexico one of the largest intact silicic volcanic provinces known. Previous models have proposed an assimilation–fractional crystallization origin for the rhyolites involving closed-system fractional crystallization from crustally contaminated andesitic parental magmas, with <20% crustal contributions. The lack of isotopic variation among the lower crustal xenoliths inferred to represent the crustal contaminants and coeval Sierra Madre Occidental rhyolite and basaltic andesite to andesite volcanic rocks has constrained interpretations for larger crustal contributions. Here, we use zircon age populations as probes to assess crustal involvement in Sierra Madre Occidental silicic magmatism. Laser ablation-inductively coupled plasma-mass spectrometry analyses of zircons from rhyolitic ignimbrites from the northeastern and southwestern sectors of the province yield U–Pb ages that show significant age discrepancies of 1–4 Myr compared with previously determined K/Ar and 40Ar/39Ar ages from the same ignimbrites; the age differences are greater than the errors attributable to analytical uncertainty. Zircon xenocrysts with new overgrowths in the Late Eocene to earliest Oligocene rhyolite ignimbrites from the northeastern sector provide direct evidence for some involvement of Proterozoic crustal materials, and, potentially more importantly, the derivation of zircon from Mesozoic and Eocene age, isotopically primitive, subduction-related igneous basement. The youngest rhyolitic ignimbrites from the southwestern sector show even stronger evidence for inheritance in the age spectra, but lack old inherited zircon (i.e. Eocene or older). Instead, these Early Miocene ignimbrites are dominated by antecrystic zircons, representing >33 to ∼100% of the dated population; most antecrysts range in age between ∼20 and 32 Ma. A sub-population of the antecrystic zircons is chemically distinct in terms of their high U (>1000 ppm to 1·3 wt %) and heavy REE contents; these are not present in the Oligocene ignimbrites in the northeastern sector of the Sierra Madre Occidental. The combination of antecryst zircon U–Pb ages and chemistry suggests that much of the zircon in the youngest rhyolites was derived by remelting of partially molten to solidified igneous rocks formed during preceding phases of Sierra Madre Occidental volcanism. Strong Zr undersaturation, and estimations for very rapid dissolution rates of entrained zircons, preclude coeval mafic magmas being parental to the rhyolite magmas by a process of lower crustal assimilation followed by closed-system crystal fractionation as interpreted in previous studies of the Sierra Madre Occidental rhyolites. Mafic magmas were more probably important in providing a long-lived heat and material flux into the crust, resulting in the remelting and recycling of older crust and newly formed igneous materials related to Sierra Madre Occidental magmatism.

A comparison of the 27-item and 12-item intolerance of uncertainty scales

The 27-item Intolerance of Uncertainty Scale (IUS) has become one of the most frequently used measure of Intolerance of Uncertainty. More recently, an abridged, 12-item version of the IUS has been developed. The current research used clinical (n = 50) and non-clinical (n = 56) samples to examine and compare the psychometric properties of both versions of the IUS. The two scales showed good internal consistency at both the total and subscale level and had satisfactory test-retest reliability. Both versions were correlated with worry and trait anxiety and had satisfactory concurrent validity. Significant differences between the scores of the clinical and non-clinical sample supported discriminant validity. Predictive validity was also supported for the two scales. Total scores, in the case of the clinical sample, and a subscale, in the case of the non-clinical sample, significantly predicted pathological worry and trait anxiety. Overall, the clinicians and researchers can use either version of the IUS with confidence, due to their sound psychometric properties.

Range sensor pose estimation

This paper presents a method of recovering the 6 DoF pose (Cartesian position and angular rotation) of a range sensor mounted on a mobile platform. The method utilises point targets in a local scene and optimises over the error between their absolute position and their apparent position as observed by the range sensor. The analysis includes an investigation into the sensitivity and robustness of the method. Practical results were collected using a SICK LRS2100 mounted on a P&H electric mining shovel and present the errors in scan data relative to an independent 3D scan of the scene. A comparison to directly measuring the sensor pose is presented and shows the significant accuracy improvements in scene reconstruction using this pose estimation method.

Incorporating parameter uncertainty into quantitative microbial risk assessment (QMRA)

Modern statistical models and computational methods can now incorporate uncertainty of the parameters used in Quantitative Microbial Risk Assessments (QMRA). Many QMRAs use Monte Carlo methods, but work from fixed estimates for means, variances and other parameters. We illustrate the ease of estimating all parameters contemporaneously with the risk assessment, incorporating all the parameter uncertainty arising from the experiments from which these parameters are estimated. A Bayesian approach is adopted, using Markov Chain Monte Carlo Gibbs sampling (MCMC) via the freely available software, WinBUGS. The method and its ease of implementation are illustrated by a case study that involves incorporating three disparate datasets into an MCMC framework. The probabilities of infection when the uncertainty associated with parameter estimation is incorporated into a QMRA are shown to be considerably more variable over various dose ranges than the analogous probabilities obtained when constants from the literature are simply ‘plugged’ in as is done in most QMRAs. Neglecting these sources of uncertainty may lead to erroneous decisions for public health and risk management.

Hierarchical Bayesian models for estimating the extent of plant pest invasions

Plant biosecurity requires statistical tools to interpret field surveillance data in order to manage pest incursions that threaten crop production and trade. Ultimately, management decisions need to be based on the probability that an area is infested or free of a pest. Current informal approaches to delimiting pest extent rely upon expert ecological interpretation of presence / absence data over space and time. Hierarchical Bayesian models provide a cohesive statistical framework that can formally integrate the available information on both pest ecology and data. The overarching method involves constructing an observation model for the surveillance data, conditional on the hidden extent of the pest and uncertain detection sensitivity. The extent of the pest is then modelled as a dynamic invasion process that includes uncertainty in ecological parameters. Modelling approaches to assimilate this information are explored through case studies on spiralling whitefly, Aleurodicus dispersus and red banded mango caterpillar, Deanolis sublimbalis. Markov chain Monte Carlo simulation is used to estimate the probable extent of pests, given the observation and process model conditioned by surveillance data. Statistical methods, based on time-to-event models, are developed to apply hierarchical Bayesian models to early detection programs and to demonstrate area freedom from pests. The value of early detection surveillance programs is demonstrated through an application to interpret surveillance data for exotic plant pests with uncertain spread rates. The model suggests that typical early detection programs provide a moderate reduction in the probability of an area being infested but a dramatic reduction in the expected area of incursions at a given time. Estimates of spiralling whitefly extent are examined at local, district and state-wide scales. The local model estimates the rate of natural spread and the influence of host architecture, host suitability and inspector efficiency. These parameter estimates can support the development of robust surveillance programs. Hierarchical Bayesian models for the human-mediated spread of spiralling whitefly are developed for the colonisation of discrete cells connected by a modified gravity model. By estimating dispersal parameters, the model can be used to predict the extent of the pest over time. An extended model predicts the climate restricted distribution of the pest in Queensland. These novel human-mediated movement models are well suited to demonstrating area freedom at coarse spatio-temporal scales. At finer scales, and in the presence of ecological complexity, exploratory models are developed to investigate the capacity for surveillance information to estimate the extent of red banded mango caterpillar. It is apparent that excessive uncertainty about observation and ecological parameters can impose limits on inference at the scales required for effective management of response programs. The thesis contributes novel statistical approaches to estimating the extent of pests and develops applications to assist decision-making across a range of plant biosecurity surveillance activities. Hierarchical Bayesian modelling is demonstrated as both a useful analytical tool for estimating pest extent and a natural investigative paradigm for developing and focussing biosecurity programs.

Uncertainty and innovation in fashion design

Generally speaking, psychologists have suggested three traditional views of how people cope with uncertainty. They are the certainty maximiser, the intuitive statistician-economist and the knowledge seeker (Smithson, 2008). In times of uncertainty, such as the recent global financial crisis, these coping methods often result in innovation in industry. Richards (2003) identifies innovation as different from creativity in that innovation aims to transform and implement rather than simply explore and invent. An examination of the work of iconic fashion designers, through case study and situational analysis, reveals that coping with uncertainty manifests itself in ways that have resulted in innovations in design, marketing methods, production and consumption. In relation to contemporary fashion, where many garments look the same in style, colour, cut and fit (Finn, 2008), the concept of innovation is an important one. This paper explores the role of uncertainty as a driver of innovation in fashion design. A key aspect of seeking knowledge, as a mechanism to cope with this uncertainty, is a return to basics. This is a problem for contemporary fashion designers who are no longer necessarily makers and therefore do not engage with the basic materials and methods of garment construction. In many cases design in fashion has become digital, communicated to an unseen, unknown production team via scanned image and specification alone. The disconnection between the design and the making of garments, as a result of decades of off-shore manufacturing, has limited the opportunity for this return to basics. The authors argue that the role of the fashion designer has become about the final product and as a result there is a lack of innovation in the process of making: in the form, fit and function of fashion garments. They propose that ‘knowledge seeking’ as a result of uncertainty in the fashion industry, in particular through re-examination of the methods of making, could hold the key to a new era of innovation in fashion design.

Adaptive GPS duty cycling and radio ranging for energy-efficient localization

This paper addresses the tradeoff between energy consumption and localization performance in a mobile sensor network application. The focus is on augmenting GPS location with more energy-efficient location sensors to bound position estimate uncertainty in order to prolong node lifetime. We use empirical GPS and radio contact data from a largescale animal tracking deployment to model node mobility, GPS and radio performance. These models are used to explore duty cycling strategies for maintaining position uncertainty within specified bounds. We then explore the benefits of using short-range radio contact logging alongside GPS as an energy-inexpensive means of lowering uncertainty while the GPS is off, and we propose a versatile contact logging strategy that relies on RSSI ranging and GPS lock back-offs for reducing the node energy consumption relative to GPS duty cycling. Results show that our strategy can cut the node energy consumption by half while meeting application specific positioning criteria.

Information sharing with key suppliers : a transaction cost theory perspective

Purpose: The purpose of this paper is to explain variations in discretionary information shared between buyers and key suppliers. The paper also aims to examine how the extent of information shared affects buyers’ performance in terms of resource usage, output, and flexibility. ----- ----- Design/methodology/approach: The data for the paper comprise 221 Finnish and Swedish non-service companies obtained through a mail survey. The hypothesized relationships were tested using partial least squares modelling with reflective and formative constructs.----- ----- Findings: The results of the study suggest that (environmental and demand) uncertainty and interdependency can to some degree explain the extent of information shared between a buyer and key supplier. Furthermore, information sharing improves buyers’ performance with respect to resource usage, output, and flexibility.----- ----- Research limitations/implications: A limitation to the paper relates to the data, which only included buyers.Abetter approach would have been to collect data from both, buyers and key suppliers. Practical implications – Companies face a wide range of supply chain solutions that enable and encourage collaboration across organizations. This paper suggests a more selective and balanced approach toward adopting the solutions offered as the benefits are contingent on a number of factors such as uncertainty. Also, the risks of information sharing are far too high for a one size fits all approach.----- ----- Originality/value: The paper illustrates the applicability of transaction cost theory to the contemporary era of e-commerce. With this finding, transaction cost economics can provide a valuable lens with which to view and interpret interorganizational information sharing, a topic that has received much attention in the recent years.

Long range relations : stakeholder engagement in Queensland road construction

This paper presents the historical and contextual background of road construction by state and local government in Queensland. It also highlights some key events that have shaped stakeholder participation in road infrastructure planning and delivery in Queensland. This synthesis was developed from a review of publications, organisational documents and interviews. To set the scene, the factors that shaped road delivery will be discussed.

How can soil monitoring networks be used to improve predictions of organic carbon pool dynamics and CO2 fluxes in agricultural soils?

Abstract As regional and continental carbon balances of terrestrial ecosystems become available, it becomes clear that the soils are the largest source of uncertainty. Repeated inventories of soil organic carbon (SOC) organized in soil monitoring networks (SMN) are being implemented in a number of countries. This paper reviews the concepts and design of SMNs in ten countries, and discusses the contribution of such networks to reducing the uncertainty of soil carbon balances. Some SMNs are designed to estimate country-specific land use or management effects on SOC stocks, while others collect soil carbon and ancillary data to provide a nationally consistent assessment of soil carbon condition across the major land-use/soil type combinations. The former use a single sampling campaign of paired sites, while for the latter both systematic (usually grid based) and stratified repeated sampling campaigns (5–10 years interval) are used with densities of one site per 10–1,040 km². For paired sites, multiple samples at each site are taken in order to allow statistical analysis, while for the single sites, composite samples are taken. In both cases, fixed depth increments together with samples for bulk density and stone content are recommended. Samples should be archived to allow for re-measurement purposes using updated techniques. Information on land management, and where possible, land use history should be systematically recorded for each site. A case study of the agricultural frontier in Brazil is presented in which land use effect factors are calculated in order to quantify the CO2 fluxes from national land use/management conversion matrices. Process-based SOC models can be run for the individual points of the SMN, provided detailed land management records are available. These studies are still rare, as most SMNs have been implemented recently or are in progress. Examples from the USA and Belgium show that uncertainties in SOC change range from 1.6–6.5 Mg C ha−1 for the prediction of SOC stock changes on individual sites to 11.72 Mg C ha−1 or 34% of the median SOC change for soil/land use/climate units. For national SOC monitoring, stratified sampling sites appears to be the most straightforward attribution of SOC values to units with similar soil/land use/climate conditions (i.e. a spatially implicit upscaling approach). Keywords Soil monitoring networks - Soil organic carbon - Modeling - Sampling design

The probability archive : essence, uncertainty, and the ‘Olduvai imperative.’

Starting from a local problem with finding an archival clip on YouTube, this paper expands to consider the nature of archives in general. It considers the technological, communicative and philosophical characteristics of archives over three historical periods: 1) Modern ‘essence archives’ – museums and galleries organised around the concept of objectivity and realism; 2) Postmodern mediation archives – broadcast TV systems, which I argue were also ‘essence archives,’ albeit a transitional form; and 3) Network or ‘probability archives’ – YouTube and the internet, which are organised around the concept of probability. The paper goes on to argue the case for introducing quantum uncertainty and other aspects of probability theory into the humanities, in order to understand the way knowledge is collected, conserved, curated and communicated in the era of the internet. It is illustrated throughout by reference to the original technological 'affordance' – the Olduvai stone chopping tool.