Synthesizing Regularity Exposing Attributes in Large Protein Databases

This thesis describes a system that synthesizes regularity exposing attributes from large protein databases. After processing primary and secondary structure data, this system discovers an amino acid representation that captures what are thought to be the three most important amino acid characteristics (size, charge, and hydrophobicity) for tertiary structure prediction. A neural network trained using this 16 bit representation achieves a performance accuracy on the secondary structure prediction problem that is comparable to the one achieved by a neural network trained using the standard 24 bit amino acid representation. In addition, the thesis describes bounds on secondary structure prediction accuracy, derived using an optimal learning algorithm and the probably approximately correct (PAC) model.

Harvesting undelimbed Scots pine (Pinus sylvestris L.) from first thinnings for integrated production of kraft pulp and energy

The present study evaluates the feasibility of undelimbed Scots pine (Pinus sylvestris L.) for integrated production of pulp and energy in a kraft pulp mill from the technical, economic and environmental points of view, focusing on the potential of bundle harvesting. The feasibility of tree sections for pulp production was tested by conducting an industrial wood-handling experiment, laboratory cooking and bleaching trials, using conventional small-diameter Scots pine pulpwood as a reference. These trials showed that undelimbed Scots pine sections can be processed in favourable conditions as a blend with conventional small-diameter pulpwood without reducing the pulp quality. However, fibre losses at various phases of the process may increase when using undelimbed material. In the economic evaluation, both pulp production and wood procurement costs were considered, using the relative wood paying capability of a kraft pulp mill as a determinant. The calculations were made for three Scots pine first-thinning stands with the breast-height diameter of the removal (6 12 cm) as the main distinctive factor. The supply chains included in the comparison were based on cut-to-length harvesting, whole-tree harvesting and bundle harvesting (whole-tree bundling). With the current ratio of pulp and energy prices, the wood paying capability declines with an increase in the proportion of the energy fraction of the raw material. The supply system based on the cut-to-length method was the most efficient option, resulting in the highest residual value at stump in most cases. A decline in the pulp price and an increase in the energy price improved the competitiveness of the whole-tree systems. With short truck transportation distances and low pulp prices, however, the harvesting of loose whole trees can result in higher residual value at stump in small-diameter stands. While savings in transportation costs did not compensate for the high cutting and compaction costs by the second prototype of the bundle harvester, an increase in transportation distances improved its competitiveness. Since harvesting undelimbed assortments increases nutrient export from the site, which can affect soil productivity, the whole-tree alternatives included in the present study cannot be recommended on infertile peatlands and mineral soils. The harvesting of loose whole trees or bundled whole trees implies a reduction in protective logging residues and an increase in site traffic or payloads. These factors increase the risk of soil damage, especially on peat soils with poor bearing capacity. Within the wood procurement parameters which were examined, the CO2 emissions of the supply systems varied from 13 27 kg m3. Compaction of whole trees into bundles reduced emissions from transportation by 30 39%, but these reductions were insufficient to compensate for the increased emissions from cutting and compaction.

Applications on fault tree analysis in railway power supply systems

Fault tree analysis (FTA) is presented to model the reliability of a railway traction power system in this paper. First, the construction of fault tree is introduced to integrate components in traction power systems into a fault tree; then the binary decision diagram (BDD) method is used to evaluate fault trees qualitatively and quantitatively. The components contributing to the reliability of overall system are identified with their relative importance through sensitivity analysis. Finally, an AC traction power system is evaluated by the proposed methods.

Tree-Based Adaptive Spatial Detection for Adaptive Modulated MIMO Systems

Adaptive Multiple-Input Multiple-Output (MIMO) systems achieve a much higher information rate than conventional fixed schemes due to their ability to adapt their configurations according to the wireless communications environment. However, current adaptive MIMO detection schemes exhibit either low performance (and hence low spectral efficiency) or huge computational
complexity. In particular, whilst deterministic Sphere Decoder (SD) detection schemes are well established for static MIMO systems, exhibiting deterministic parallel structure, low computational complexity and quasi-ML detection performance, there are no corresponding adaptive schemes. This paper solves
this problem, describing a hybrid tree based adaptive modulation detection scheme. Fixed Complexity Sphere Decoding (FSD) and Real-Values FSD (RFSD) are modified and combined into a hybrid scheme exploited at low and medium SNR to provide the highest possible information rate with quasi-ML Bit Error
Rate (BER) performance, while Reduced Complexity RFSD, BChase and Decision Feedback (DFE) schemes are exploited in the high SNR regions. This algorithm provides the facility to balance the detection complexity with BER performance with compatible information rate in dynamic, adaptive MIMO communications
environments.

Competition in tree row agroforestry systems. 3. Soil water distribution and dynamics

The purpose of this study was to test the hypothesis that soil water content would vary spatially with distance from a tree row and that the effect would differ according to tree species. A field study was conducted on a kaolinitic Oxisol in the sub-humid highlands of western Kenya to compare soil water distribution and dynamics in a maize monoculture with that under maize (Zea mays L.) intercropped with a 3-year-old tree row of Grevillea robusta A. Cunn. Ex R. Br. (grevillea) and hedgerow of Senna spectabilis DC. (senna). Soil water content was measured at weekly intervals during one cropping season using a neutron probe. Measurements were made from 20 cm to a depth of 225 cm at distances of 75, 150, 300 and 525 cm from the tree rows. The amount of water stored was greater under the sole maize crop than the agroforestry systems, especially the grevillea-maize system. Stored soil water in the grevillea-maize system increased with increasing distance from the tree row but in the senna-maize system, it decreased between 75 and 300 cm from the hedgerow. Soil water content increased least and more slowly early in the season in the grevillea-maize system, and drying was also evident as the frequency of rain declined. Soil water content at the end of the cropping season was similar to that at the start of the season in the grevillea-maize system, but about 50 and 80 mm greater in the senna-maize and sole maize systems, respectively. The seasonal water balance showed there was 140 mm, of drainage from the sole maize system. A similar amount was lost from the agroforestry systems (about 160 mm in the grevillea-maize system and 145 mm in the senna-maize system) through drainage or tree uptake. The possible benefits of reduced soil evaporation and crop transpiration close to a tree row were not evident in the grevillea-maize system, but appeared to greatly compensate for water uptake losses in the senna-maize system. Grevillea, managed as a tree row, reduced stored soil water to a greater extent than senna, managed as a hedgerow.

Growth parameters and nutrient content in four multipurpose tree species with potential characteristics for agroforestry systems in a Cerrado region in Botucatu, São Paulo State, Brazil

In order to evaluate growth characteristics, adaptability, biomass production, nutrient recycling, nutrient distribution and the ability to regenerate degraded land, a trial using four multipurpose tree species (Leucaena leucocephala, Leucaena diversifolia, Acacia melanoxylon and Mimosa scabrella) was undertaken over two years in a distrophic red yellow latosol (oxisol) following a randomized block experimental design with four replications. At the age of two years, A. melanoxylon and L. diversifolia were the tallest species (5.25 and 4.97 m, respectively) and A. melanoxylon and M. scabrella had the largest diameters at 20 cm from tree base. Mimosa scabrella and A. melanoxylon had the highest dry matter production and quantity of nutrients in the above ground biomass. In all species, the highest nutrient contents were found in the leaves, followed by branches and stems. From all species, the highest Nutrient Utilization Efficiency Indexes were obtained for sulphur, phosphorous, and magnesium; L. diversifolia was the most efficient for nitrogen, potassium, calcium, sulphur, and manganese, while A. melanoxylon was the most efficient for phosphorus, magnesium, boron, iron, and zinc. Litter production levels over a three month period were as follows: M. scabrella > A. melanoxylon > L. diversifolia > L. leucocephala. Litter nutrient content was higher in M. scabrella than in the other species.

Starch distribution in pear tree organs in relation to training systems, rootstocks and fruit quality

Starch is the main form in which plants store carbohydrates reserves, both in terms of amounts and distribution among different plant species. Carbohydrates are direct products of photosynthetic activity, and it is well know that yield efficiency and production are directly correlated to the amount of carbohydrates synthesized and how these are distributed among vegetative and reproductive organs. Nowadays, in pear trees, due to the modernization of orchards, through the introduction of new rootstocks and the development of new training systems, the understanding and the development of new approaches regarding the distribution and storage of carbohydrates, are required. The objective of this research work was to study the behavior of carbohydrate reserves, mainly starch, in different pear tree organs and tissues: i.e., fruits, leaves, woody organs, roots and flower buds, at different physiological stages during the season. Starch in fruit is accumulated at early stages, and reached a maximum concentration during the middle phase of fruit development; after that, its degradation begins with a rise in soluble carbohydrates. Moreover, relationships between fruit starch degradation and different fruit traits, soluble sugars and organic acids were established. In woody organs and roots, an interconversion between starch and soluble carbohydrates was observed during the dormancy period that confirms its main function in supporting the growth and development of new tissues during the following spring. Factors as training systems, rootstocks, types of bearing wood, and their position on the canopy, influenced the concentrations of starch and soluble carbohydrates at different sampling dates. Also, environmental conditions and cultural practices must be considered to better explain these results. Thus, a deeper understanding of the dynamics of carbohydrates reserves within the plant could provide relevant information to improve several management practices to increase crop yield efficiency.

Carbon stocks, tree diversity, and the role of organic certification in different cocoa production systems in Alto Beni, Bolivia

This study compares aboveground and belowground carbon stocks and tree diversity in different cocoa cultivation systems in Bolivia: monoculture, simple agroforestry, and successional agroforestry, as well as fallow as a control. Since diversified, agroforestry-based cultivation systems are often considered important for sustainable development, we also evaluated the links between carbon stocks and tree diversity, as well as the role of organic certification in transitioning from monoculture to agroforestry. Biomass, tree diversity, and soil physiochemical parameters were sampled in 15 plots measuring 48 × 48 m. Semi-structured interviews with 52 cocoa farmers were used to evaluate the role of organic certification and farmers’ organizations (e.g., cocoa cooperatives) in promoting tree diversity. Total carbon stocks in simple agroforestry systems (128.4 ± 20 Mg ha−1) were similar to those on fallow plots (125.2 ± 10 Mg ha−1). Successional agroforestry systems had the highest carbon stocks (143.7 ± 5.3 Mg ha−1). Monocultures stored significantly less carbon than all other systems (86.3 ± 4.0 Mg ha−1, posterior probability P(Diff > 0) of 0.000–0.006). Among shade tree species, Schizolobium amazonicum, Centrolobium ochroxylum, and Anadenanthera sp. accumulated the most biomass. High-value timber species (S. amazonicum, C. ochroxylum, Amburana cearensis, and Swietenia macrophylla) accounted for 22.0 % of shade tree biomass. The Shannon index and tree species richness were highest in successional agroforestry systems. Cocoa plots on certified organic farms displayed significantly higher tree species richness than plots on non-certified farms. Thus, expanding the coverage of organic farmers’ organizations may be an effective strategy for fostering transitions from monoculture to agroforestry systems.

The management oversight and risk tree-MORT : including systems developed by the Idaho Operations Office and Aerojet Nuclear Company,

"February 12, 1973."

Classical simulation of quantum many-body systems with a tree tensor network

We show how to efficiently simulate a quantum many-body system with tree structure when its entanglement (Schmidt number) is small for any bipartite split along an edge of the tree. As an application, we show that any one-way quantum computation on a tree graph can be efficiently simulated with a classical computer.

Expert systems for fault tree synthesis

Hazard and operability (HAZOP) studies on chemical process plants are very time consuming, and often tedious, tasks. The requirement for HAZOP studies is that a team of experts systematically analyse every conceivable process deviation, identifying possible causes and any hazards that may result. The systematic nature of the task, and the fact that some team members may be unoccupied for much of the time, can lead to tedium, which in turn may lead to serious errors or omissions. An aid to HAZOP are fault trees, which present the system failure logic graphically such that the study team can readily assimilate their findings. Fault trees are also useful to the identification of design weaknesses, and may additionally be used to estimate the likelihood of hazardous events occurring. The one drawback of fault trees is that they are difficult to generate by hand. This is because of the sheer size and complexity of modern process plants. The work in this thesis proposed a computer-based method to aid the development of fault trees for chemical process plants. The aim is to produce concise, structured fault trees that are easy for analysts to understand. Standard plant input-output equation models for major process units are modified such that they include ancillary units and pipework. This results in a reduction in the nodes required to represent a plant. Control loops and protective systems are modelled as operators which act on process variables. This modelling maintains the functionality of loops, making fault tree generation easier and improving the structure of the fault trees produced. A method, called event ordering, is proposed which allows the magnitude of deviations of controlled or measured variables to be defined in terms of the control loops and protective systems with which they are associated.

Application of K-tree to document clustering

Digital collections are growing exponentially in size as the information age takes a firm grip on all aspects of society. As a result Information Retrieval (IR) has become an increasingly important area of research. It promises to provide new and more effective ways for users to find information relevant to their search intentions. Document clustering is one of the many tools in the IR toolbox and is far from being perfected. It groups documents that share common features. This grouping allows a user to quickly identify relevant information. If these groups are misleading then valuable information can accidentally be ignored. There- fore, the study and analysis of the quality of document clustering is important. With more and more digital information available, the performance of these algorithms is also of interest. An algorithm with a time complexity of O(n2) can quickly become impractical when clustering a corpus containing millions of documents. Therefore, the investigation of algorithms and data structures to perform clustering in an efficient manner is vital to its success as an IR tool. Document classification is another tool frequently used in the IR field. It predicts categories of new documents based on an existing database of (doc- ument, category) pairs. Support Vector Machines (SVM) have been found to be effective when classifying text documents. As the algorithms for classifica- tion are both efficient and of high quality, the largest gains can be made from improvements to representation. Document representations are vital for both clustering and classification. Representations exploit the content and structure of documents. Dimensionality reduction can improve the effectiveness of existing representations in terms of quality and run-time performance. Research into these areas is another way to improve the efficiency and quality of clustering and classification results. Evaluating document clustering is a difficult task. Intrinsic measures of quality such as distortion only indicate how well an algorithm minimised a sim- ilarity function in a particular vector space. Intrinsic comparisons are inherently limited by the given representation and are not comparable between different representations. Extrinsic measures of quality compare a clustering solution to a “ground truth” solution. This allows comparison between different approaches. As the “ground truth” is created by humans it can suffer from the fact that not every human interprets a topic in the same manner. Whether a document belongs to a particular topic or not can be subjective.