Geochemistry from the S1 tephra of core GeoTü SL112 and samples from Erciyes Dag eruptions Dikkartin, Karagüllü and Perikartin

A hitherto unknown distal volcanic ash layer has been detected in a sediment core recovered from the southeastern Levantine Sea (Eastern Mediterranean Sea). Radiometric, stratigraphical and sedimentological data show that the tephra, here termed as S1 tephra, was deposited between 8,970 and 8,690 cal yr BP. The high-silica rhyolitic composition excludes an origin from any known eruptions of the Italian, Aegean or Arabian volcanic provinces but suggests a prevailing Central Anatolian provenance. We compare the S1 tephra with proximal to medial-distal tephra deposits from well-known Mediterranean ash layers and ash fall deposits from the Central Anatolian volcanic field using electron probe microanalyses on volcanic glass shards and morphological analyses on ash particles. We postulate a correlation with the Early Holocene 'Dikkartin' dome eruption of Erciyes Dag volcano (Cappadocia, Turkey). So far, no tephra of the Central Anatolian volcanic province has been detected in marine sediment archives in the Eastern Mediterranean region. The occurrence of the S1 tephra in the south-eastern part of the Levantine Sea indicates a wide dispersal of pyroclastic material from Erciyes Dag more than 600 km to the south and is therefore an important tephrostratigraphical marker in sediments of the easternmost Mediterranean Sea and the adjacent hinterland.

Vergelyking van den republicaenschen met den gregoriaenschen almanach : beginnende van den 1sten Vendemiaire jaer 1 (22 September 1792) dag zyn'er stichtinge, tot den 10 Nivose jaer 14 (laesten December 1805) inclus, tydstip zyn'er vernieting /

Mode of access: Internet.

"I dag"; kåserier. Femte samlingen.

Mode of access: Internet.

Hver 8 dag; illustreret ugeskrift.

Title varies: 1894-1896, Hver 14 dag; illustreret tidskrift, 1897- , Hver 8 dag; illustreret ugeskrift.

Schriftmatig vertoog over Lucas 2:vs.13.14 : Benevens voorbereidselen, waar in ondersogt werdt de eigentlyke dag van de Geboorte van onsen Heiland Jesus Christus. /

Mode of access: Internet.

Lífs-Saga Jóns Jónssonar fordum Sýslumanns i Rángárvalla-sýslu, upplesin vid hanns útfør ad Odda, dag 4. Septembris 1789.

Mode of access: Internet.

The development of a serological-based diagnostic test for Dasheen mosaic potyvirus (DsMV)

Dasheen mosaic potyvirus (DsMV) is an important virus affecting taro. The virus has been found wherever taro is grown and infects both the edible and ornamental aroids, causing yield losses of up to 60%. The presence of DsMV, and other viruses,prevents the international movement of taro germplasm between countries. This has a significant negative impact on taro production in many countries due to the inability to access improved taro lines produced in breeding programs. To overcome this problem, sensitive and reliable virus diagnostic tests need to be developed to enable the indexing of taro germplasm. The aim of this study was to generate an antiserum against a recombinant DsMV coat protein (CP) and to develop a serological-based diagnostic test that would detect Pacific Island isolates of the virus. The CP-coding region of 16 DsMV isolates from Papua New Guinea, Samoa, Solomon Islands, French Polynesia, New Caledonia and Vietnam were amplified,cloned and sequenced. The size of the CP-coding region ranged from 939 to 1038 nucleotides and encoded putative proteins ranged from 313 to 346 amino acids, with the molecular mass ranging from 34 to 38 kDa. Analysis ofthe amino acid sequences revealed the presence of several amino acid motifs typically found in potyviruses,including DAG, WCIE/DN, RQ and AFDF. When the amino acid sequences were compared with each other and the DsMV sequences on the database, the maximum variability was21.9%. When the core region ofthe CP was analysed, the maximum variability dropped to 6% indicating most variability was present in the N terminus. Within seven PNG isolates ofDsMV, the maximum variability was 16.9% and 3.9% over the entire CP-coding region and core region, respectively. The sequence ofPNG isolate P1 was most similar to all other sequences. Phylogenetic analysis indicated that almost all isolates grouped according to their provenance. Further, the seven PNG isolates were grouped according to the region within PNG from which they were obtained. Due to the extensive variability over the entire CP-coding region, the core region ofthe CP ofPNG isolate Pl was cloned into a protein expression vector and expressed as a recombinant protein. The protein was purified by chromatography and SDS-PAGE and used as an antigen to generate antiserum in a rabbit. In western blots, the antiserum reacted with bands of approximately 45-47 kDa in extracts from purified DsMV and from known DsMV -infected plants from PNG; no bands were observed using healthy plant extracts. The antiserum was subsequently incorporated into an indirect ELISA. This procedure was found to be very sensitive and detected DsMV in sap diluted at least 1:1,000. Using both western blot and ELISA formats,the antiserum was able to detect a wide range ofDsMV isolates including those from Australia, New Zealand, Fiji, French Polynesia, New Caledonia, Papua New Guinea, Samoa, Solomon Islands and Vanuatu. These plants were verified to be infected with DsMV by RT-PCR. In specificity tests, the antiserum was also found to react with sap from plants infected with SCMV, PRSV-P, PRSV-W, but not with PVY or CMV -infected plants.

Discussions on conceptual knowledge and the use of blogs

In both Australia and Norway and through a number of Technology projects conducted since 2007, the authors – together and with other collaborators - have attempted to create positive learning environments supported by Web 2.0 communication tools. Through protected public sites and the oz-Teachernet [http://www.otn.edu.au], we have consistently chosen to use blogs to support the social construction of knowledge, that is, to allow students the opportunity to discuss, share and collaborate on their classroom activities and engagement with Technology artefacts and processes. Through comparisons with findings from a small-scale project in Norway and a large-scale project in Australia, this paper will argue for the potential of discussion through blogs but recommend that the purposeful use of scientific language in student communication will not occur without teacher intervention and scaffolding.

Using Bayesian methods for the estimation of uncertainty in complex statistical models

The research objectives of this thesis were to contribute to Bayesian statistical methodology by contributing to risk assessment statistical methodology, and to spatial and spatio-temporal methodology, by modelling error structures using complex hierarchical models. Specifically, I hoped to consider two applied areas, and use these applications as a springboard for developing new statistical methods as well as undertaking analyses which might give answers to particular applied questions. Thus, this thesis considers a series of models, firstly in the context of risk assessments for recycled water, and secondly in the context of water usage by crops. The research objective was to model error structures using hierarchical models in two problems, namely risk assessment analyses for wastewater, and secondly, in a four dimensional dataset, assessing differences between cropping systems over time and over three spatial dimensions. The aim was to use the simplicity and insight afforded by Bayesian networks to develop appropriate models for risk scenarios, and again to use Bayesian hierarchical models to explore the necessarily complex modelling of four dimensional agricultural data. The specific objectives of the research were to develop a method for the calculation of credible intervals for the point estimates of Bayesian networks; to develop a model structure to incorporate all the experimental uncertainty associated with various constants thereby allowing the calculation of more credible credible intervals for a risk assessment; to model a single day’s data from the agricultural dataset which satisfactorily captured the complexities of the data; to build a model for several days’ data, in order to consider how the full data might be modelled; and finally to build a model for the full four dimensional dataset and to consider the timevarying nature of the contrast of interest, having satisfactorily accounted for possible spatial and temporal autocorrelations. This work forms five papers, two of which have been published, with two submitted, and the final paper still in draft. The first two objectives were met by recasting the risk assessments as directed, acyclic graphs (DAGs). In the first case, we elicited uncertainty for the conditional probabilities needed by the Bayesian net, incorporated these into a corresponding DAG, and used Markov chain Monte Carlo (MCMC) to find credible intervals, for all the scenarios and outcomes of interest. In the second case, we incorporated the experimental data underlying the risk assessment constants into the DAG, and also treated some of that data as needing to be modelled as an ‘errors-invariables’ problem [Fuller, 1987]. This illustrated a simple method for the incorporation of experimental error into risk assessments. In considering one day of the three-dimensional agricultural data, it became clear that geostatistical models or conditional autoregressive (CAR) models over the three dimensions were not the best way to approach the data. Instead CAR models are used with neighbours only in the same depth layer. This gave flexibility to the model, allowing both the spatially structured and non-structured variances to differ at all depths. We call this model the CAR layered model. Given the experimental design, the fixed part of the model could have been modelled as a set of means by treatment and by depth, but doing so allows little insight into how the treatment effects vary with depth. Hence, a number of essentially non-parametric approaches were taken to see the effects of depth on treatment, with the model of choice incorporating an errors-in-variables approach for depth in addition to a non-parametric smooth. The statistical contribution here was the introduction of the CAR layered model, the applied contribution the analysis of moisture over depth and estimation of the contrast of interest together with its credible intervals. These models were fitted using WinBUGS [Lunn et al., 2000]. The work in the fifth paper deals with the fact that with large datasets, the use of WinBUGS becomes more problematic because of its highly correlated term by term updating. In this work, we introduce a Gibbs sampler with block updating for the CAR layered model. The Gibbs sampler was implemented by Chris Strickland using pyMCMC [Strickland, 2010]. This framework is then used to consider five days data, and we show that moisture in the soil for all the various treatments reaches levels particular to each treatment at a depth of 200 cm and thereafter stays constant, albeit with increasing variances with depth. In an analysis across three spatial dimensions and across time, there are many interactions of time and the spatial dimensions to be considered. Hence, we chose to use a daily model and to repeat the analysis at all time points, effectively creating an interaction model of time by the daily model. Such an approach allows great flexibility. However, this approach does not allow insight into the way in which the parameter of interest varies over time. Hence, a two-stage approach was also used, with estimates from the first-stage being analysed as a set of time series. We see this spatio-temporal interaction model as being a useful approach to data measured across three spatial dimensions and time, since it does not assume additivity of the random spatial or temporal effects.

Letter from Zambia

An 800-word travel article about the Dag Hammarskjold Memorial site in Ndola, Zambia.