A new approach to soil classification mapping based on the spatial distribution of soil properties

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Bandit-Based Algorithms for Budgeted Learning

We explore the problem of budgeted machine learning, in which the learning algorithm has free access to the training examples’ labels but has to pay for each attribute that is specified. This learning model is appropriate in many areas, including medical applications. We present new algorithms for choosing which attributes to purchase of which examples in the budgeted learning model based on algorithms for the multi-armed bandit problem. All of our approaches outperformed the current state of the art. Furthermore, we present a new means for selecting an example to purchase after the attribute is selected, instead of selecting an example uniformly at random, which is typically done. Our new example selection method improved performance of all the algorithms we tested, both ours and those in the literature.

Mid- to late-Holocene paleoceanographic changes on the southeastern Brazilian shelf based on grain size records

; High-resolution grain size analyses of three AMS (14)C-dated cores from the Southeastern Brazilian shelf provide a detailed record of mid- to late-Holocene environmental changes in the Southwestern Atlantic Margin. The cores exhibit millennial variability that we associate with the previously described southward shift of the Inter Tropical Convergence Zone (ITCZ) average latitudinal position over the South American continent during the Holocene climatic maximum. This generated changes in the wind-driven current system of the SW Atlantic margin and modified the grain size characteristics of the sediments deposited there. Centennial variations in the grain size are associated with a previously described late-Holocene enhancement of the El Nino-Southern Oscillation (ENSO) amplitude, which led to stronger NNE trade winds off eastern Brazil, favouring SW transport of sediments from the Paraiba do Sul River. This is recorded in a core from off Cabo Frio as a coarsening trend from 3000 cal. BP onwards. The ENSO enhancement also caused changes in precipitation and wind pattern in southern Brazil, allowing high discharge events and northward extensions of the low-saline water plume from Rio de la Plata. We propose that this resulted in a net increase in northward alongshore transport of fine sediments, seen as a prominent fine-shift at 2000 cal. BP in a core from similar to 24 degrees S on the Brazilian shelf. Wavelet-and spectral analysis of the sortable silt records show a significant similar to 1000-yr periodicity, which we attribute to solar forcing. If correct, this is one of the first indications of solar forcing of this timescale on the Southwestern Atlantic margin.

NMR Based Foodomics to Investigate the Digestibility of Protein-Rich Food Products

Nowadays, in developed countries, the excessive food intake, in conjunction with a decreased physical activity, has led to an increase in lifestyle-related diseases, such as obesity, cardiovascular diseases, type -2 diabetes, a range of cancer types and arthritis. The socio-economic importance of such lifestyle-related diseases has encouraged countries to increase their efforts in research, and many projects have been initiated recently in research that focuses on the relationship between food and health. Thanks to these efforts and to the growing availability of technologies, the food companies are beginning to develop healthier food. The necessity of rapid and affordable methods, helping the food industries in the ingredient selection has stimulated the development of in vitro systems that simulate the physiological functions to which the food components are submitted when administrated in vivo. One of the most promising tool now available appears the in vitro digestion, which aims at predicting, in a comparative way among analogue food products, the bioaccessibility of the nutrients of interest.. The adoption of the foodomics approach has been chosen in this work to evaluate the modifications occurring during the in vitro digestion of selected protein-rich food products. The measure of the proteins breakdown was performed via NMR spectroscopy, the only techniques capable of observing, directly in the simulated gastric and duodenal fluids, the soluble oligo- and polypeptides released during the in vitro digestion process. The overall approach pioneered along this PhD work, has been discussed and promoted in a large scientific community, with specialists networked under the INFOGEST COST Action, which recently released a harmonized protocol for the in vitro digestion. NMR spectroscopy, when used in tandem with the in vitro digestion, generates a new concept, which provides an additional attribute to describe the food quality: the comparative digestibility, which measures the improvement of the nutrients bioaccessibility.

Detection of Mycoplasma mycoides subsp. mycoides SC in bronchoalveolar lavage fluids of cows based on a TaqMan real-time PCR discriminating wild type strains from an lppQ(-) mutant vaccine strain used for DIVA-strategies

Contagious bovine pleuropneumonia (CBPP) is the most serious cattle disease in Africa, caused by Mycoplasma mycoides subsp. mycoides small-colony type (SC). CBPP control strategies currently rely on vaccination with a vaccine based on live attenuated strains of the organism. Recently, an lppQ(-) mutant of the existing vaccine strain T1/44 has been developed (Janis et al., 2008). This T1lppQ(-) mutant strain is devoid of lipoprotein LppQ, a potential virulence attribute of M. mycoides subsp. mycoides SC. It is designated as a potential live DIVA (Differentiating Infected from Vaccinated Animals) vaccine strain allowing both serological and etiological differentiation. The present paper reports on the validation of a control strategy for CBPP in cattle, whereby a TaqMan real-time PCR based on the lppQ gene has been developed for the direct detection of M. mycoides subsp. mycoides SC in ex vivo bronchoalveolar lavage fluids of cows and for the discrimination of wild type strains from the lppQ(-) mutant vaccine strain.

Ice-Core Based Assessment of Historical Anthropogenic Heavy Metal (Cd, Cu, Sb, Zn) Emissions in the Soviet Union

The development of strategies and policies aiming at the reduction of environmental exposure to air pollution requires the assessment of historical emissions. Although anthropogenic emissions from the extended territory of the Soviet Union (SU) considerably influenced concentrations of heavy metals in the Northern Hemisphere, Pb is the only metal with long-term historical emission estimates for this region available, whereas for selected other metals only single values exist. Here we present the first study assessing long-term Cd, Cu, Sb, and Zn emissions in the SU during the period 1935–1991 based on ice-core concentration records from Belukha glacier in the Siberian Altai and emission data from 12 regions in the SU for the year 1980. We show that Zn primarily emitted from the Zn production in Ust-Kamenogorsk (East Kazakhstan) dominated the SU heavy metal emission. Cd, Sb, Zn (Cu) emissions increased between 1935 and the 1970s (1980s) due to expanded non-ferrous metal production. Emissions of the four metals in the beginning of the 1990s were as low as in the 1950s, which we attribute to the economic downturn in industry, changes in technology for an increasing metal recovery from ores, the replacement of coal and oil by gas, and air pollution control.

PartsList: a web-based system for dynamically ranking protein folds based on disparate attributes, including whole-genome expression and interaction information

As the number of protein folds is quite limited, a mode of analysis that will be increasingly common in the future, especially with the advent of structural genomics, is to survey and re-survey the finite parts list of folds from an expanding number of perspectives. We have developed a new resource, called PartsList, that lets one dynamically perform these comparative fold surveys. It is available on the web at http://bioinfo.mbb.yale.edu/partslist and http://www.partslist.org. The system is based on the existing fold classifications and functions as a form of companion annotation for them, providing ‘global views’ of many already completed fold surveys. The central idea in the system is that of comparison through ranking; PartsList will rank the approximately 420 folds based on more than 180 attributes. These include: (i) occurrence in a number of completely sequenced genomes (e.g. it will show the most common folds in the worm versus yeast); (ii) occurrence in the structure databank (e.g. most common folds in the PDB); (iii) both absolute and relative gene expression information (e.g. most changing folds in expression over the cell cycle); (iv) protein–protein interactions, based on experimental data in yeast and comprehensive PDB surveys (e.g. most interacting fold); (v) sensitivity to inserted transposons; (vi) the number of functions associated with the fold (e.g. most multi-functional folds); (vii) amino acid composition (e.g. most Cys-rich folds); (viii) protein motions (e.g. most mobile folds); and (ix) the level of similarity based on a comprehensive set of structural alignments (e.g. most structurally variable folds). The integration of whole-genome expression and protein–protein interaction data with structural information is a particularly novel feature of our system. We provide three ways of visualizing the rankings: a profiler emphasizing the progression of high and low ranks across many pre-selected attributes, a dynamic comparer for custom comparisons and a numerical rankings correlator. These allow one to directly compare very different attributes of a fold (e.g. expression level, genome occurrence and maximum motion) in the uniform numerical format of ranks. This uniform framework, in turn, highlights the way that the frequency of many of the attributes falls off with approximate power-law behavior (i.e. according to V–b, for attribute value V and constant exponent b), with a few folds having large values and most having small values.

Validation of the Item-Attribute Matrix in TIMSS-Mathematics Using Multiple Regression and the LSDM

The purposes of this study were (1) to validate of the item-attribute matrix using two levels of attributes (Level 1 attributes and Level 2 sub-attributes), and (2) through retrofitting the diagnostic models to the mathematics test of the Trends in International Mathematics and Science Study (TIMSS), to evaluate the construct validity of TIMSS mathematics assessment by comparing the results of two assessment booklets. Item data were extracted from Booklets 2 and 3 for the 8th grade in TIMSS 2007, which included a total of 49 mathematics items and every student's response to every item. The study developed three categories of attributes at two levels: content, cognitive process (TIMSS or new), and comprehensive cognitive process (or IT) based on the TIMSS assessment framework, cognitive procedures, and item type. At level one, there were 4 content attributes (number, algebra, geometry, and data and chance), 3 TIMSS process attributes (knowing, applying, and reasoning), and 4 new process attributes (identifying, computing, judging, and reasoning). At level two, the level 1 attributes were further divided into 32 sub-attributes. There was only one level of IT attributes (multiple steps/responses, complexity, and constructed-response). Twelve Q-matrices (4 originally specified, 4 random, and 4 revised) were investigated with eleven Q-matrix models (QM1 ~ QM11) using multiple regression and the least squares distance method (LSDM). Comprehensive analyses indicated that the proposed Q-matrices explained most of the variance in item difficulty (i.e., 64% to 81%). The cognitive process attributes contributed to the item difficulties more than the content attributes, and the IT attributes contributed much more than both the content and process attributes. The new retrofitted process attributes explained the items better than the TIMSS process attributes. Results generated from the level 1 attributes and the level 2 attributes were consistent. Most attributes could be used to recover students' performance, but some attributes' probabilities showed unreasonable patterns. The analysis approaches could not demonstrate if the same construct validity was supported across booklets. The proposed attributes and Q-matrices explained the items of Booklet 2 better than the items of Booklet 3. The specified Q-matrices explained the items better than the random Q-matrices.

The evaluation of the spatial and temporal stability of sugarcane farm performance based on yield and commercial cane sugar

In broader catchment scale investigations, there is a need to understand and ultimately exploit the spatial variation of agricultural crops for an improved economic return. In many instances, this spatial variation is temporally unstable and may be different for various crop attributes and crop species. In the Australian sugar industry, the opportunity arose to evaluate the performance of 231 farms in the Tully Mill area in far north Queensland using production information on cane yield (t/ha) and CCS ( a fresh weight measure of sucrose content in the cane) accumulated over a 12-year period. Such an arrangement of data can be expressed as a 3-way array where a farm x attribute x year matrix can be evaluated and interactions considered. Two multivariate techniques, the 3-way mixture method of clustering and the 3-mode principal component analysis, were employed to identify meaningful relationships between farms that performed similarly for both cane yield and CCS. In this context, farm has a spatial component and the aim of this analysis was to determine if systematic patterns in farm performance expressed by cane yield and CCS persisted over time. There was no spatial relationship between cane yield and CCS. However, the analysis revealed that the relationship between farms was remarkably stable from one year to the next for both attributes and there was some spatial aggregation of farm performance in parts of the mill area. This finding is important, since temporally consistent spatial variation may be exploited to improve regional production. Alternatively, the putative causes of the spatial variation may be explored to enhance the understanding of sugarcane production in the wet tropics of Australia.

A risk-based model for inspection and maintenance of cross-country petroleum pipeline

The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is both time-wasting and expensive. A risk-based model that reduces the amount of time spent on inspection has been presented. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests efficient design and operation philosophy, construction methodology and logical insurance plans. The risk-based model uses Analytic Hierarchy Process (AHP), a multiple attribute decision-making technique, to identify the factors that influence failure on specific segments and analyzes their effects by determining probability of risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost, and the cumulative effect of failure is determined through probability analysis. The technique does not totally eliminate subjectivity, but it is an improvement over the existing inspection method.

Risk based decision support system for effective implementation of projects

Conventional project management techniques are not always sufficient to ensure time, cost and quality achievement of large-scale construction projects due to complexity in planning, design and implementation processes. The main reasons for project non-achievement are changes in scope and design, changes in government policies and regulations, unforeseen inflation, underestimation and improper estimation. Projects that are exposed to such an uncertain environment can be effectively managed with the application of risk management throughout the project's life cycle. However, the effectiveness of risk management depends on the technique through which the effects of risk factors are analysed/quantified. This study proposes the Analytic Hierarchy Process (AHP), a multiple attribute decision making technique, as a tool for risk analysis because it can handle subjective as well as objective factors in a decision model that are conflicting in nature. This provides a decision support system (DSS) to project management for making the right decision at the right time for ensuring project success in line with organisation policy, project objectives and a competitive business environment. The whole methodology is explained through a case application of a cross-country petroleum pipeline project in India and its effectiveness in project management is demonstrated.

Risk-based model aids selection of pipeline inspection, maintenance strategies

The existing method of pipeline monitoring, which requires an entire pipeline to be inspected periodically, wastes time and is expensive. A risk-based model that reduces the amount of time spent on inspection has been developed. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests an efficient design and operation philosophy, construction method and logical insurance plans.The risk-based model uses analytic hierarchy process, a multiple attribute decision-making technique, to identify factors that influence failure on specific segments and analyze their effects by determining the probabilities of risk factors. The severity of failure is determined through consequence analysis, which establishes the effect of a failure in terms of cost caused by each risk factor and determines the cumulative effect of failure through probability analysis.

Long-haul transmission performance evaluation of ultra-long Raman fibre laser based amplification influenced by second order co-pumping

A transmission performance investigation using ultra-long Raman fibre laser based amplification with different co-pump power is presented. We attribute Q2 factor degradation to RIN of co-pump and induced fibre laser as well as increased SBS.

Establishing Correspondences between Attribute Spaces and Complex Concept Spaces Using Meta-PGN Classifier

In this paper, we present one approach for extending the learning set of a classification algorithm with additional metadata. It is used as a base for giving appropriate names to found regularities. The analysis of correspondence between connections established in the attribute space and existing links between concepts can be used as a test for creation of an adequate model of the observed world. Meta-PGN classifier is suggested as a possible tool for establishing these connections. Applying this approach in the field of content-based image retrieval of art paintings provides a tool for extracting specific feature combinations, which represent different sides of artists' styles, periods and movements.

Evaluation of 100G DP-QPSK long-haul transmission performance using second order co-pumped Raman laser based amplification

We present, for the first time, a detailed investigation of the impact of second order co-propagating Raman pumping on long-haul 100G WDM DP-QPSK coherent transmission of up to 7082 km using Raman fibre laser based configurations. Signal power and noise distributions along the fibre for each pumping scheme were characterised both numerically and experimentally. Based on these pumping schemes, the Q factor penalties versus co-pump power ratios were experimentally measured and quantified. A significant Q factor penalty of up to 4.15 dB was observed after 1666 km using symmetric bidirectional pumping, compared with counter-pumping only. Our results show that whilst using co-pumping minimises the intra-cavity signal power variation and amplification noise, the Q factor penalty with co-pumping was too great for any advantage to be seen. The relative intensity noise (RIN) characteristics of the induced fibre laser and the output signal, and the intra-cavity RF spectra of the fibre laser are also presented. We attribute the Q factor degradation to RIN induced penalty due to RIN being transferred from the first order fibre laser and second order co-pump to the signal. More importantly, there were two different fibre lasing regimes contributing to the amplification. It was random distributed feedback lasing when using counter-pumping only and conventional Fabry-Perot cavity lasing when using all bidirectional pumping schemes. This also results in significantly different performances due to different laser cavity lengths for these two classes of laser.