Increasing detection rate of user-to-root attacks using genetic algorithms

An extensive set of machine learning and pattern classification techniques trained and tested on KDD dataset failed in detecting most of the user-to-root attacks. This paper aims to provide an approach for mitigating negative aspects of the mentioned dataset, which led to low detection rates. Genetic algorithm is employed to implement rules for detecting various types of attacks. Rules are formed of the features of the dataset identified as the most important ones for each attack type. In this way we introduce high level of generality and thus achieve high detection rates, but also gain high reduction of the system training time. Thenceforth we re-check the decision of the user-to- root rules with the rules that detect other types of attacks. In this way we decrease the false-positive rate. The model was verified on KDD 99, demonstrating higher detection rates than those reported by the state- of-the-art while maintaining low false-positive rate.

Characterization of Actinomyces isolates from infected root canals of teeth: description of Actinomyces radicidentis sp. nov.

Two strains of a previously undescribed Actinomyces-like bacterium were recovered in pure culture from infected root canals of teeth. Analysis by biochemical testing and polyacrylamide gel electrophoresis of whole-cell proteins indicated that the strains closely resembled each other phenotypically but were distinct from previously described Actinomyces and Arcanobacterium species. Comparative 16S rRNA gene-sequencing studies showed the bacterium to be a hitherto unknown subline within a group of Actinomyces species which includes Actinomyces bovis, the type species of the genus. Based on phylogenetic and phenotypic evidence, we propose that the unknown bacterium isolated from human clinical specimens be classified as Actinomyces radicidentis sp. nov. The type strain of Actinomyces radicidentis is CCUG 36733.

Fine root biomass and turnover in southern taiga estimated by root inclusion nets

Fine roots play an important part in forest carbon, nutrient and water cycles. The turnover of fine roots constitutes a major carbon input to soils. Estimation of fine root turnover is difficult, labour intensive and is often compounded by artefacts created by soil disturbance. In this work, an alternative approach of using inclusion nets installed in an undisturbed soil profile was used to measure fine root production and was compared to the in-growth core method. There was no difference between fine root production estimated by the two methods in three southern taiga sites with contrasting soil conditions and tree species composition in the Central Forest State Biosphere Reserve, Russia. Expressed as annual production over standing biomass, Norway spruce fine root turnover was in the region of 0.10 to 0.24 y-1. The inclusion net technique is suitable for field based assessment of fine root production. There are several advantages over the in-growth core method, due to non-disturbance of the soil profile and its potential for very high rate of replication.

Fine root condition relates to visible crown damage in Norway spruce on acidified soils

Allochthonous Norway spruce stands in the Kysucké Beskydy Mts. (north-western Slovakia) have been exposed to substantial acid deposition in the recent past and grow in acidified soil conditions with mean pH of about 4.0 in the topsoil. We selected 90 spruce trees representing 30 triples of different crown status: healthy, stressed and declining to assess the relationship between crown and fine root status. Sequential coring and in-growth bags were applied to each triplet to investigate fine root biomass and growth in the soil depths of 0-10 and 10-20 cm. Fine root quantity (biomass and necromass), turnover (production over standing stock), morphological features (specific root length, root tip density) and chemical properties (Ca:Al molar ratio) were compared among the abovementioned health status categories. Living fine root biomass decreased with increasing stress, while the ratio of living to dead biomass increased. Annual fine root production decreased and specific root length increased in stressed trees when compared to healthy or declining trees, a situation which may be related to the position of trees in the canopy (healthy and declining – dominant, stressed – co-dominant). The Ca:Al ratio decreased with increasing crown damage, indicating a decreased ability to filter out aluminium. In conclusion, fine root status appears to be linked to visible crown damage and can be used as a tree health indicator.

LC-MS & DFT investigations of Cryptolepis sanginolenta root extracts

The roots of Crytolepis sanguinolenta, a medicinally important ethanobotanical source of the antimalarial cryptolepine, were soxhlet extracted in anaerobic conditions, using hexane then ethanol. Samples of each extract were fractioned using flash chromatography and preparative TLC and compound identity was established using gradient HPLC-positive ion electrospray mass spectrometry. The use of argon depressed the formation of quindoline and hydroxycrytolepine. In addition to known compounds such as cryptolepine, several as yet unidentified compounds remain to be characterised in this root extract.

Ornamental Mediterranean plants in the UK: root adaptations to hypoxia and anoxia

Mediterranean species are popular landscape plants in the UK and well suited to the predicted climate change scenarios of hotter, drier summers. What is less clear is how these species will respond to the more unpredictable rainfall patterns also anticipated, where soil water-logging may become more prevalent, especially in urban environments where soil sealing can restrict drainage. Pot experiments on flooding of four Mediterranean species (Cistus × hybridus, Lavandula angustifolia ‘Munstead’, Salvia officinalis and Stachys byzantina) showed that the effects of waterlogging were only severe when the temperature was high and flooding prolonged. All plants survived the flooding in winter, but during the summer a 17-day flood resulted in the death of 30-40% of the Salvia officinalis and Cistus × hybridus. To examine the response of roots to oxygen deprivation over a range of conditions from total absence of oxygen (anoxia), low oxygen (hypoxia) and full aeration, rooted cuttings of Salvia officinalis were grown in a hydroponic-based system and mixtures of oxygen and nitrogen gases bubbled through the media. Anoxia was found to reduce root development dramatically. When the plants were subjected to a period of hypoxia they responded by increasing the production of lateral roots close to the surface thus enabling them to acclimate to subsequent anoxia. This greatly increased their chances of survival.

Testing for a unit root in a process exhibiting a structural break in the presence of GARCH errors

This paper considers the effect of GARCH errors on the tests proposed byPerron (1997) for a unit root in the presence of a structural break. We assessthe impact of degeneracy and integratedness of the conditional varianceindividually and find that, apart from in the limit, the testing procedure isinsensitive to the degree of degeneracy but does exhibit an increasingover-sizing as the process becomes more integrated. When we consider the GARCHspecifications that we are likely to encounter in empirical research, we findthat the Perron tests are reasonably robust to the presence of GARCH and donot suffer from severe over-or under-rejection of a correct null hypothesis.

Fine root turnover

Fine roots constitute an interface between plants and soils and thus play a crucial part in forest carbon, nutrient and water cycles. Their continuous growth and dieback, often termed turnover of fine roots, may constitute a major carbon input to soils and significantly contribute to belowground carbon cycle. For this reason, it is of importance to accurately estimate not only the standing biomass of fine roots, but also its rate of turnover. To date, no direct and reliable method of measuring fine root turnover exists. The main reason for this is that the two component processes of root turnover, namely growth and dieback of fine roots, nearly always happen in the same place and at the same time. Further, the estimation of fine root turnover is complicated by the inaccessibility of tree root systems, its labour intensiveness and is often compounded by artefacts created by soil disturbance. Despite the fact that the elucidation of the patterns and controls of forest fine root turnover is of utmost importance for the development of realistic carbon cycle models, our knowledge of the contribution of fine root turnover to carbon and nutrient cycles in forests remains uncertain. This chapter will detail all major methods currently used for estimating fine root turnover and highlight their advantages, as well as drawbacks.

Arabidopsis annexin1 mediates the radical-activated plasma membrane Ca2+ - and K+ -permeable conductance in root cells

Plant cell growth and stress signaling require Ca2+ influx through plasma membrane transport proteins that are regulated by reactive oxygen species. In root cell growth, adaptation to salinity stress, and stomatal closure, such proteins operate downstream of the plasma membrane NADPH oxidases that produce extracellular superoxide anion, a reactive oxygen species that is readily converted to extracellular hydrogen peroxide and hydroxyl radicals, OH_. In root cells, extracellular OH_ activates a plasma membrane Ca2+-permeable conductance that permits Ca2+ influx. In Arabidopsis thaliana, distribution of this conductance resembles that of annexin1 (ANN1). Annexins are membrane binding proteins that can form Ca2+-permeable conductances in vitro. Here, the Arabidopsis loss-of-function mutant for annexin1 (Atann1) was found to lack the root hair and epidermal OH_-activated Ca2+- and K+-permeable conductance. This manifests in both impaired root cell growth and ability to elevate root cell cytosolic free Ca2+ in response to OH_. An OH_-activated Ca2+ conductance is reconstituted by recombinant ANN1 in planar lipid bilayers. ANN1 therefore presents as a novel Ca2+-permeable transporter providing a molecular link between reactive oxygen species and cytosolic Ca2+ in plants.

Root growth models: towards a new generation of continuous approaches

Models of root system growth emerged in the early 1970s, and were based on mathematical representations of root length distribution in soil. The last decade has seen the development of more complex architectural models and the use of computer-intensive approaches to study developmental and environmental processes in greater detail. There is a pressing need for predictive technologies that can integrate root system knowledge, scaling from molecular to ensembles of plants. This paper makes the case for more widespread use of simpler models of root systems based on continuous descriptions of their structure. A new theoretical framework is presented that describes the dynamics of root density distributions as a function of individual root developmental parameters such as rates of lateral root initiation, elongation, mortality, and gravitropsm. The simulations resulting from such equations can be performed most efficiently in discretized domains that deform as a result of growth, and that can be used to model the growth of many interacting root systems. The modelling principles described help to bridge the gap between continuum and architectural approaches, and enhance our understanding of the spatial development of root systems. Our simulations suggest that root systems develop in travelling wave patterns of meristems, revealing order in otherwise spatially complex and heterogeneous systems. Such knowledge should assist physiologists and geneticists to appreciate how meristem dynamics contribute to the pattern of growth and functioning of root systems in the field.

Elevated atmospheric carbon dioxide impairs the performance of root-feeding vine weevils by modifying root growth and secondary metabolites

Predicting how insect crop pests will respond to global climate change is an important part of increasing crop production for future food security, and will increasingly rely on empirically based evidence. The effects of atmospheric composition, especially elevated carbon dioxide (eCO(2)), on insect herbivores have been well studied, but this research has focussed almost exclusively on aboveground insects. However, responses of root-feeding insects to eCO(2) are unlikely to mirror these trends because of fundamental differences between aboveground and belowground habitats. Moreover, changes in secondary metabolites and defensive responses to insect attack under eCO(2) conditions are largely unexplored for root herbivore interactions. This study investigated how eCO(2) (700 mu mol mol-1) affected a root-feeding herbivore via changes to plant growth and concentrations of carbon (C), nitrogen (N) and phenolics. This study used the root-feeding vine weevil, Otiorhynchus sulcatus and the perennial crop, Ribes nigrum. Weevil populations decreased by 33% and body mass decreased by 23% (from 7.2 to 5.4 mg) in eCO(2). Root biomass decreased by 16% in eCO(2), which was strongly correlated with weevil performance. While root N concentrations fell by 8%, there were no significant effects of eCO(2) on root C and N concentrations. Weevils caused a sink in plants, resulting in 8-12% decreases in leaf C concentration following herbivory. There was an interactive effect of CO(2) and root herbivory on root phenolic concentrations, whereby weevils induced an increase at ambient CO(2), suggestive of defensive response, but caused a decrease under eCO(2). Contrary to predictions, there was a positive relationship between root phenolics and weevil performance. We conclude that impaired root-growth underpinned the negative effects of eCO(2) on vine weevils and speculate that the plant's failure to mount a defensive response at eCO(2) may have intensified these negative effects.

Root phenomics of crops: opportunities and challenges

Reliable techniques for screening large numbers of plants for root traits are still being developed, but include aeroponic, hydroponic and agar plate systems. Coupled with digital cameras and image analysis software, these systems permit the rapid measurement of root numbers, length and diameter in moderate ( typically <1000) numbers of plants. Usually such systems are employed with relatively small seedlings, and information is recorded in 2D. Recent developments in X-ray microtomography have facilitated 3D non-invasive measurement of small root systems grown in solid media, allowing angular distributions to be obtained in addition to numbers and length. However, because of the time taken to scan samples, only a small number can be screened (typically<10 per day, not including analysis time of the large spatial datasets generated) and, depending on sample size, limited resolution may mean that fine roots remain unresolved. Although agar plates allow differences between lines and genotypes to be discerned in young seedlings, the rank order may not be the same when the same materials are grown in solid media. For example, root length of dwarfing wheat ( Triticum aestivum L.) lines grown on agar plates was increased by similar to 40% relative to wild-type and semi-dwarfing lines, but in a sandy loam soil under well watered conditions it was decreased by 24-33%. Such differences in ranking suggest that significant soil environment-genotype interactions are occurring. Developments in instruments and software mean that a combination of high-throughput simple screens and more in-depth examination of root-soil interactions is becoming viable.

Advances in sequential data assimilation and numerical weather forecasting: an Ensemble Transform Kalman-Bucy Filter, a study on clustering in deterministic Ensemble Square Root Filters, and a test of a new time stepping scheme in an atmospheric model

This dissertation deals with aspects of sequential data assimilation (in particular ensemble Kalman filtering) and numerical weather forecasting. In the first part, the recently formulated Ensemble Kalman-Bucy (EnKBF) filter is revisited. It is shown that the previously used numerical integration scheme fails when the magnitude of the background error covariance grows beyond that of the observational error covariance in the forecast window. Therefore, we present a suitable integration scheme that handles the stiffening of the differential equations involved and doesn’t represent further computational expense. Moreover, a transform-based alternative to the EnKBF is developed: under this scheme, the operations are performed in the ensemble space instead of in the state space. Advantages of this formulation are explained. For the first time, the EnKBF is implemented in an atmospheric model. The second part of this work deals with ensemble clustering, a phenomenon that arises when performing data assimilation using of deterministic ensemble square root filters in highly nonlinear forecast models. Namely, an M-member ensemble detaches into an outlier and a cluster of M-1 members. Previous works may suggest that this issue represents a failure of EnSRFs; this work dispels that notion. It is shown that ensemble clustering can be reverted also due to nonlinear processes, in particular the alternation between nonlinear expansion and compression of the ensemble for different regions of the attractor. Some EnSRFs that use random rotations have been developed to overcome this issue; these formulations are analyzed and their advantages and disadvantages with respect to common EnSRFs are discussed. The third and last part contains the implementation of the Robert-Asselin-Williams (RAW) filter in an atmospheric model. The RAW filter is an improvement to the widely popular Robert-Asselin filter that successfully suppresses spurious computational waves while avoiding any distortion in the mean value of the function. Using statistical significance tests both at the local and field level, it is shown that the climatology of the SPEEDY model is not modified by the changed time stepping scheme; hence, no retuning of the parameterizations is required. It is found the accuracy of the medium-term forecasts is increased by using the RAW filter.