The largest volcanic eruptions on Earth

Large igneous provinces (LIPs) are sites of the most frequently recurring, largest volume basaltic and silicic eruptions in Earth history. These large-volume (N1000 km3 dense rock equivalent) and large-magnitude (NM8) eruptions produce areally extensive (104–105 km2) basaltic lava flow fields and silicic ignimbrites that are the main building blocks of LIPs. Available information on the largest eruptive units are primarily from the Columbia River and Deccan provinces for the dimensions of flood basalt eruptions, and the Paraná–Etendeka and Afro-Arabian provinces for the silicic ignimbrite eruptions. In addition, three large-volume (675– 2000 km3) silicic lava flows have also been mapped out in the Proterozoic Gawler Range province (Australia), an interpreted LIP remnant. Magma volumes of N1000 km3 have also been emplaced as high-level basaltic and rhyolitic sills in LIPs. The data sets indicate comparable eruption magnitudes between the basaltic and silicic eruptions, but due to considerable volumes residing as co-ignimbrite ash deposits, the current volume constraints for the silicic ignimbrite eruptions may be considerably underestimated. Magma composition thus appears to be no barrier to the volume of magma emitted during an individual eruption. Despite this general similarity in magnitude, flood basaltic and silicic eruptions are very different in terms of eruption style, duration, intensity, vent configuration, and emplacement style. Flood basaltic eruptions are dominantly effusive and Hawaiian–Strombolian in style, with magma discharge rates of ~106–108 kg s−1 and eruption durations estimated at years to tens of years that emplace dominantly compound pahoehoe lava flow fields. Effusive and fissural eruptions have also emplaced some large-volume silicic lavas, but discharge rates are unknown, and may be up to an order of magnitude greater than those of flood basalt lava eruptions for emplacement to be on realistic time scales (b10 years). Most silicic eruptions, however, are moderately to highly explosive, producing co-current pyroclastic fountains (rarely Plinian) with discharge rates of 109– 1011 kg s−1 that emplace welded to rheomorphic ignimbrites. At present, durations for the large-magnitude silicic eruptions are unconstrained; at discharge rates of 109 kg s−1, equivalent to the peak of the 1991 Mt Pinatubo eruption, the largest silicic eruptions would take many months to evacuate N5000 km3 of magma. The generally simple deposit structure is more suggestive of short-duration (hours to days) and high intensity (~1011 kg s−1) eruptions, perhaps with hiatuses in some cases. These extreme discharge rates would be facilitated by multiple point, fissure and/or ring fracture venting of magma. Eruption frequencies are much elevated for large-magnitude eruptions of both magma types during LIP-forming episodes. However, in basaltdominated provinces (continental and ocean basin flood basalt provinces, oceanic plateaus, volcanic rifted margins), large magnitude (NM8) basaltic eruptions have much shorter recurrence intervals of 103–104 years, whereas similar magnitude silicic eruptions may have recurrence intervals of up to 105 years. The Paraná– Etendeka province was the site of at least nine NM8 silicic eruptions over an ~1 Myr period at ~132 Ma; a similar eruption frequency, although with a fewer number of silicic eruptions is also observed for the Afro- Arabian Province. The huge volumes of basaltic and silicic magma erupted in quick succession during LIP events raises several unresolved issues in terms of locus of magma generation and storage (if any) in the crust prior to eruption, and paths and rates of ascent from magma reservoirs to the surface.

Survey of novice motorcycle riders and their riding experience before licensing

Graduated licensing schemes have been found to reduce the crash risk of young novice drivers, but there is less evidence of their success with novice motorcycle riders. This study examined the riding experience of a sample of Australian learner-riders to establish the extent and variety of their riding practice during the learner stage. Riders completed an anonymous questionnaire at a compulsory rider-training course for the licensing test. The majority of participants were male (81%) with an average age of 33 years. They worked full time (81%), held an unrestricted driver's license (81%), and owned the motorcycle that they rode (79%). These riders had held their learner's license for an average of 6 months. On average, they rode 6.4 h/week. By the time they attempted the rider-licensing test, they had ridden a total of 101 h. Their total hours of on-road practice were comparable to those of learner-drivers at the same stage of licensing, but they had less experience in adverse or challenging road conditions. A substantial proportion had little or no experience of riding in the rain (57%), at night (36%), in heavy traffic (22%), on winding rural roads (52%), or on high-speed roads (51%). These findings highlight the differences in the learning processes between unsupervised novice motorcycle riders and supervised novice drivers. Further research is necessary to clarify whether specifying the conditions under which riders should practice during the graduated licensing process would likely reduce or increase their crash risk.

Visuospatial tasks suppress craving for cigarettes

The Elaborated Intrusion (EI) theory of desire posits that visual imagery plays a key role in craving. We report a series of experiments testing this hypothesis in a drug addiction context. Experiment 1 showed that a mental visual imagery task with neutral content reduced cigarette craving in abstaining smokers, but that an equivalent auditory task did not. The effect of visual imagery was replicated in Experiment 2, which also showed comparable effects of non-imagery visual working memory interference. Experiment 3 showed that the benefit of visual over auditory interference was not dependent upon imagery being used to induce craving. Experiment 4 compared a visuomotor task, making shapes from modeling clay, with a verbal task (counting back from 100), and again showed a benefit of the visual over the non-visual task. We conclude that visual imagery supports craving for cigarettes. Competing imagery or visual working memory tasks may help tackle craving in smokers trying to quit.

Agroinoculation Allows the Screening of Rice for Resistance to Rice Tungro Bacilliform Virus

A system for agroinoculating rice tungro bacilliform virus (RTBV), one of the two viruses of the rice tungro disease complex, has been optimised. A nontumour-inducing strain of Agrobacterium (pGV3850) was used in order to conform with biosafety regulations. Fourteen-day-old seedlings survived the mechanical damage of the technique and were still young enough to support virus replication. The level of the bacterial inoculum was important to obtain maximum infection, with a high inoculum level (0.5 × 1012 cells/ml) resulting in up to 100% infection of a susceptible variety that was comparable with infection by insect transmission. Agroinoculation with RTBV was successful for all three rice cultivarss tested; TN1 (tungro susceptible), Balimau Putih (tungro tolerant), and IR26 (RTSV and vector resistant). Agroinoculation enables resistance to RTBV to be distinguished from resistance to the leafhopper vector of the virus, and should prove useful in screening rice germplasm, breeding materials, and transgenic rice lines.

Procuring Sydney’s Olympic Stadium : a world class event?

This paper describes and analyses the procurement processes employed in delivering the Sydney Olympic Stadium – arguably the most significant stadia project in the region today. This current high profile project is discussed in terms of a case study into the procurement processes used. Interviews, personal site visits and questionnaires were used to obtain information on the procurement processes used and comments on their application to the project. The alternative procurement process used on this project—Design and Construction within a Build, Own, Operate and Transfer (BOOT) project—is likely to impact on the construction industry as a whole. Already other projects and sectors are following this lead. Based on a series of on-site interviews and questionnaires, a series of benefits and drawbacks to this procurement strategy are provided.The Olympic Stadium project has also been further analysed during construction through a Degree of Interaction framework to determine anticipated project success. This analysis investigates project interaction and user satisfaction to provide a comparable rating. A series of questionnaires were used to collect data to calculate the Degree of Interaction and User Satisfaction ratings.

Mechanical conditions in the initial phase of bone healing

Background: Bone healing is sensitive to the initial mechanical conditions with tissue differentiation being determined within days of trauma. Whilst axial compression is regarded as stimulatory, the role of interfragmentary shear is controversial. The purpose of this study was to determine how the initial mechanical conditions produced by interfragmentary shear and torsion differ from those produced by axial compressive movements. ----- ----- Methods: The finite element method was used to estimate the strain, pressure and fluid flow in the early callus tissue produced by the different modes of interfragmentary movement found in vivo. Additionally, tissue formation was predicted according to three principally different mechanobiological theories. ----- ----- Findings: Large interfragmentary shear movements produced comparable strains and less fluid flow and pressure than moderate axial interfragmentary movements. Additionally, combined axial and shear movements did not result in overall increases in the strains and the strain magnitudes were similar to those produced by axial movements alone. Only when axial movements where applied did the non-distortional component of the pressure–deformation theory influence the initial tissue predictions. ----- ----- Interpretation: This study found that the mechanical stimuli generated by interfragmentary shear and torsion differed from those produced by axial interfragmentary movements. The initial tissue formation as predicted by the mechanobiological theories was dominated by the deformation stimulus.

A material model for flexural crack simulation in reinforced concrete elements using ABAQUS

This paper presents a material model to simulate load induced cracking in Reinforced Concrete (RC) elements in ABAQUS finite element package. Two numerical material models are used and combined to simulate complete stress-strain behaviour of concrete under compression and tension including damage properties. Both numerical techniques used in the present material model are capable of developing the stress-strain curves including strain softening regimes only using ultimate compressive strength of concrete, which is easily and practically obtainable for many of the existing RC structures or those to be built. Therefore, the method proposed in this paper is valuable in assessing existing RC structures in the absence of more detailed test results. The numerical models are slightly modified from the original versions to be comparable with the damaged plasticity model used in ABAQUS. The model is validated using different experiment results for RC beam elements presented in the literature. The results indicate a good agreement with load vs. displacement curve and observed crack patterns.

Machine learning techniques to improve software quality

A significant proportion of the cost of software development is due to software testing and maintenance. This is in part the result of the inevitable imperfections due to human error, lack of quality during the design and coding of software, and the increasing need to reduce faults to improve customer satisfaction in a competitive marketplace. Given the cost and importance of removing errors improvements in fault detection and removal can be of significant benefit. The earlier in the development process faults can be found, the less it costs to correct them and the less likely other faults are to develop. This research aims to make the testing process more efficient and effective by identifying those software modules most likely to contain faults, allowing testing efforts to be carefully targeted. This is done with the use of machine learning algorithms which use examples of fault prone and not fault prone modules to develop predictive models of quality. In order to learn the numerical mapping between module and classification, a module is represented in terms of software metrics. A difficulty in this sort of problem is sourcing software engineering data of adequate quality. In this work, data is obtained from two sources, the NASA Metrics Data Program, and the open source Eclipse project. Feature selection before learning is applied, and in this area a number of different feature selection methods are applied to find which work best. Two machine learning algorithms are applied to the data - Naive Bayes and the Support Vector Machine - and predictive results are compared to those of previous efforts and found to be superior on selected data sets and comparable on others. In addition, a new classification method is proposed, Rank Sum, in which a ranking abstraction is laid over bin densities for each class, and a classification is determined based on the sum of ranks over features. A novel extension of this method is also described based on an observed polarising of points by class when rank sum is applied to training data to convert it into 2D rank sum space. SVM is applied to this transformed data to produce models the parameters of which can be set according to trade-off curves to obtain a particular performance trade-off.

Mining positive and negative patterns for relevance feature discovery

It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of the large number of terms, patterns, and noise. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern-based methods should perform better than term-based ones in describing user preferences, but many experiments do not support this hypothesis. The innovative technique presented in paper makes a breakthrough for this difficulty. This technique discovers both positive and negative patterns in text documents as higher level features in order to accurately weight low-level features (terms) based on their specificity and their distributions in the higher level features. Substantial experiments using this technique on Reuters Corpus Volume 1 and TREC topics show that the proposed approach significantly outperforms both the state-of-the-art term-based methods underpinned by Okapi BM25, Rocchio or Support Vector Machine and pattern based methods on precision, recall and F measures.

Rough sets based reasoning and pattern mining for a two-stage information filtering system

This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern- based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experiments have been conducted to compare the proposed two-stage filtering (T-SM) model with other possible "term-based + pattern-based" or "term-based + term-based" IF models. The results based on the RCV1 corpus show that the T-SM model significantly outperforms other types of "two-stage" IF models.

Selected new training documents to update user profile

Relevance Feedback (RF) has been proven very effective for improving retrieval accuracy. Adaptive information filtering (AIF) technology has benefited from the improvements achieved in all the tasks involved over the last decades. A difficult problem in AIF has been how to update the system with new feedback efficiently and effectively. In current feedback methods, the updating processes focus on updating system parameters. In this paper, we developed a new approach, the Adaptive Relevance Features Discovery (ARFD). It automatically updates the system's knowledge based on a sliding window over positive and negative feedback to solve a nonmonotonic problem efficiently. Some of the new training documents will be selected using the knowledge that the system currently obtained. Then, specific features will be extracted from selected training documents. Different methods have been used to merge and revise the weights of features in a vector space. The new model is designed for Relevance Features Discovery (RFD), a pattern mining based approach, which uses negative relevance feedback to improve the quality of extracted features from positive feedback. Learning algorithms are also proposed to implement this approach on Reuters Corpus Volume 1 and TREC topics. Experiments show that the proposed approach can work efficiently and achieves the encouragement performance.

What aspects of the scoliosis correction are most important to the teenager who has keyhole scoliosis correction surgery? A prospective series of 100 patients

Introduction. Surgical treatment of scoliosis is assessed in the spine clinic by the surgeon making numerous measurements on X-Rays as well as the rib hump. But it is important to understand which of these measures correlate with self-reported improvements in patients’ quality of life following surgery. The objective of this study was to examine the relationship between patient satisfaction after thoracoscopic (keyhole) anterior scoliosis surgery and standard deformity correction measures using the Scoliosis Research Society (SRS) adolescent questionnaire. Methods. A series of 100 consecutive adolescent idiopathic scoliosis patients received a single anterior rod via a keyhole approach at the Mater Children’s Hospital, Brisbane. Patients completed SRS outcomes questionnaires before surgery and again at 24 months after surgery. Multiple regression and t-tests were used to investigate the relationship between SRS scores and deformity correction achieved after surgery. Results. There were 94 females and 6 males with a mean age of 16.1 years. The mean Cobb angle improved from 52º pre-operatively to 21º for the instrumented levels post-operatively (59% correction) and the mean rib hump improved from 16º to 8º (51% correction). The mean total SRS score for the cohort was 99.4/120 which indicated a high level of satisfaction with the results of their scoliosis surgery. None of the deformity related parameters in the multiple regressions were significant. However, the twenty patients with the smallest Cobb angles after surgery reported significantly higher SRS scores than the twenty patients with the largest Cobb angles after surgery, but there was no difference on the basis of rib hump correction. Discussion. Patients undergoing thoracoscopic (keyhole) anterior scoliosis correction report good SRS scores which are comparable to those in previous studies. We suggest that the absence of any statistically significant difference in SRS scores between patients with and without rod or screw complications is because these complications are not associated with any clinically significant loss of correction in our patient group. The Cobb angle after surgery was the only significant predictor of patient satisfaction when comparing subgroups of patients with the largest and smallest Cobb angles after surgery.