Spatial variability of the chemical, physical and biological properties in lowland cultivated with irrigated rice

In the areas where irrigated rice is grown in the south of Brazil, few studies have been carried out to investigate the spatial variability structure of soil properties and to establish new forms of soil management as well as determine soil corrective and fertilizer applications. In this sense, this study had the objective of evaluating the spatial variability of chemical, physical and biological soil properties in a lowland area under irrigated rice cultivation in the conventional till system. For this purpose, a 10 x 10 m grid of 100 points was established, in an experimental field of the Embrapa Clima Temperado, in the County of Capão do Leão, State of Rio Grande do Sul. The spatial variability structure was evaluated by geostatistical tools and the number of subsamples required to represent each soil property in future studies was calculated using classical statistics. Results showed that the spatial variability structure of sand, silt, SMP index, cation exchange capacity (pH 7.0), Al3+ and total N properties could be detected by geostatistical analysis. A pure nugget effect was observed for the nutrients K, S and B, as well as macroporosity, mean weighted diameter of aggregates, and soil water storage. The cross validation procedure, based on linear regression and the determination coefficient, was more efficient to evaluate the quality of the adjusted mathematical model than the degree of spatial dependence. It was also concluded that the combination of classical with geostatistics can in many cases simplify the soil sampling process without losing information quality.

The functional and biological properties of whey proteins : prospects for the development of functional foods

Selostus: Heraproteiinit terveysvaikutteisten elintarvikkeiden kehittämisessä

BIO-INSPIRED COMPUTATIONAL TECHNIQUES APPLIED TO THE CLUSTERING AND VISUALIZATION OF SPATIO-TEMPORAL GEOSPATIAL DATA

The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.

Analysis of micro- and nano-structures of the corneal surface of Drosophila and its mutants by atomic force microscopy and optical diffraction.

Drosophila melanogaster is a model organism instrumental for numerous biological studies. The compound eye of this insect consists of some eight hundred individual ommatidia or facets, ca. 15 µm in cross-section. Each ommatidium contains eighteen cells including four cone cells secreting the lens material (cornea). High-resolution imaging of the cornea of different insects has demonstrated that each lens is covered by the nipple arrays--small outgrowths of ca. 200 nm in diameter. Here we for the first time utilize atomic force microscopy (AFM) to investigate nipple arrays of the Drosophila lens, achieving an unprecedented visualization of the architecture of these nanostructures. We find by Fourier analysis that the nipple arrays of Drosophila are disordered, and that the seemingly ordered appearance is a consequence of dense packing of the nipples. In contrast, Fourier analysis confirms the visibly ordered nature of the eye microstructures--the individual lenses. This is different in the frizzled mutants of Drosophila, where both Fourier analysis and optical imaging detect disorder in lens packing. AFM reveals intercalations of the lens material between individual lenses in frizzled mutants, providing explanation for this disorder. In contrast, nanostructures of the mutant lens show the same organization as in wild-type flies. Thus, frizzled mutants display abnormal organization of the corneal micro-, but not nano-structures. At the same time, nipples of the mutant flies are shorter than those of the wild-type. We also analyze corneal surface of glossy-appearing eyes overexpressing Wingless--the lipoprotein ligand of Frizzled receptors, and find the catastrophic aberration in nipple arrays, providing experimental evidence in favor of the major anti-reflective function of these insect eye nanostructures. The combination of the easily tractable genetic model organism and robust AFM analysis represents a novel methodology to analyze development and architecture of these surface formations.

Seeds enriched with phosphorus and molybdenum improve the contribution of biological nitrogen fixation to common bean as estimated by 15n isotope dilution

Seeds with a high concentration of P or Mo can improve the growth and N accumulation of the common bean (Phaseolus vulgaris L.), but the effect of enriched seeds on biological N2 fixation has not been established yet. This study aimed to evaluate the effect of seeds enriched with P and Mo on growth and biological N2 fixation of the common bean by the 15N isotope dilution technique. An experiment was carried out in pots in a 2 x 3 x 2 x 2 factorial design in randomized blocks with four replications, comprising two levels of soil applied P (0 and 80 mg kg-1), three N sources (without N, inoculated with rhizobia, and mineral N), two seed P concentrations (low and high), and two seed Mo concentrations (low and high). Non-nodulating bean and sorghum were used as non-fixing crops. The substrate was 5.0 kg of a Red Latosol (Oxisol) previously enriched with 15N and mixed with 5.0 kg of sand. Plants were harvested 41 days after emergence. Seeds with high P concentration increased the growth and N in shoots, particularly in inoculated plants at lower applied P levels. Inoculated plants raised from high P seeds showed improved nodulation at both soil P levels. Higher soil P levels increased the percentage of N derived from the atmosphere (%Ndfa) in bean leaves. Inoculation with the selected strains increased the %Ndfa. High seed P increased the %Ndfa in inoculated plants at lower soil P levels. High seed Mo increased the %Ndfa at lower soil P levels in plants that did not receive inoculation or mineral N. It is concluded that high seed P concentration increases the growth, N accumulation and the contribution of the biological N2 fixation in the common bean, particularly in inoculated plants grown at lower soil P availability.

Insertion of green fluorescent protein into nonstructural protein 5A allows direct visualization of functional hepatitis C virus replication complexes.

Hepatitis C virus (HCV) replicates its genome in a membrane-associated replication complex, composed of viral proteins, replicating RNA and altered cellular membranes. We describe here HCV replicons that allow the direct visualization of functional HCV replication complexes. Viable replicons selected from a library of Tn7-mediated random insertions in the coding sequence of nonstructural protein 5A (NS5A) allowed the identification of two sites near the NS5A C terminus that tolerated insertion of heterologous sequences. Replicons encoding green fluorescent protein (GFP) at these locations were only moderately impaired for HCV RNA replication. Expression of the NS5A-GFP fusion protein could be demonstrated by immunoblot, indicating that the GFP was retained during RNA replication and did not interfere with HCV polyprotein processing. More importantly, expression levels were robust enough to allow direct visualization of the fusion protein by fluorescence microscopy. NS5A-GFP appeared as brightly fluorescing dot-like structures in the cytoplasm. By confocal laser scanning microscopy, NS5A-GFP colocalized with other HCV nonstructural proteins and nascent viral RNA, indicating that the dot-like structures, identified as membranous webs by electron microscopy, represent functional HCV replication complexes. These findings reveal an unexpected flexibility of the C-terminal domain of NS5A and provide tools for studying the formation and turnover of HCV replication complexes in living cells.

Evidence of climatic niche shift during biological invasion

Niche-based models calibrated in the native range by relating species observations to climatic variables are commonly used to predict the potential spatial extent of species' invasion. This climate matching approach relies on the assumption that invasive species conserve their climatic niche in the invaded ranges. We test this assumption by analysing the climatic niche spaces of Spotted Knapweed in western North America and Europe. We show with robust cross-continental data that a shift of the observed climatic niche occurred between native and non-native ranges, providing the first empirical evidence that an invasive species can occupy climatically distinct niche spaces following its introduction into a new area. The models fail to predict the current invaded distribution, but correctly predict areas of introduction. Climate matching is thus a useful approach to identify areas at risk of introduction and establishment of newly or not-yet-introduced neophytes, but may not predict the full extent of invasions.

Application of Visualization and Simulation Program to Improve Work Zone Safety and Mobility, January 2010

A previous study sponsored by the Smart Work Zone Deployment Initiative, “Feasibility of Visualization and Simulation Applications to Improve Work Zone Safety and Mobility,” demonstrated the feasibility of combining readily available, inexpensive software programs, such as SketchUp and Google Earth, with standard two-dimensional civil engineering design programs, such as MicroStation, to create animations of construction work zones. The animations reflect changes in work zone configurations as the project progresses, representing an opportunity to visually present complex information to drivers, construction workers, agency personnel, and the general public. The purpose of this study is to continue the work from the previous study to determine the added value and resource demands created by including more complex data, specifically traffic volume, movement, and vehicle type. This report describes the changes that were made to the simulation, including incorporating additional data and converting the simulation from a desktop application to a web application.

History of biological warfare and bioterrorism.

Bioterrorism literally means using microorganisms or infected samples to cause terror and panic in populations. Bioterrorism had already started 14 centuries before Christ, when the Hittites sent infected rams to their enemies. However, apart from some rare well-documented events, it is often very difficult for historians and microbiologists to differentiate natural epidemics from alleged biological attacks, because: (i) little information is available for times before the advent of modern microbiology; (ii) truth may be manipulated for political reasons, especially for a hot topic such as a biological attack; and (iii) the passage of time may also have distorted the reality of the past. Nevertheless, we have tried to provide to clinical microbiologists an overview of some likely biological warfare that occurred before the 18th century and that included the intentional spread of epidemic diseases such as tularaemia, plague, malaria, smallpox, yellow fever, and leprosy. We also summarize the main events that occurred during the modern microbiology era, from World War I to the recent 'anthrax letters' that followed the World Trade Center attack of September 2001. Again, the political polemic surrounding the use of infectious agents as a weapon may distort the truth. This is nicely exemplified by the Sverdlovsk accident, which was initially attributed by the authorities to a natural foodborne outbreak, and was officially recognized as having a military cause only 13 years later.

Gene expression signatures delineate biological and prognostic subgroups in peripheral T-cell lymphoma

Peripheral T-cell lymphoma (PTCL) encompasses a heterogeneous group of neoplasms with generally poor clinical outcome. Currently 50% of PTCL cases are not classifiable: PTCL-not otherwise specified (NOS). Gene-expression profiles on 372 PTCL cases were analyzed and robust molecular classifiers and oncogenic pathways that reflect the pathobiology of tumor cells and their microenvironment were identified for major PTCL-entities, including 114 angioimmunoblastic T-cell lymphoma (AITL), 31 anaplastic lymphoma kinase (ALK)-positive and 48 ALK-negative anaplastic large cell lymphoma, 14 adult T-cell leukemia/lymphoma and 44 extranodal NK/T-cell lymphoma that were further separated into NK-cell and gdT-cell lymphomas. Thirty-seven percent of morphologically diagnosed PTCL-NOS cases were reclassified into other specific subtypes by molecular signatures. Reexamination, immunohistochemistry, and IDH2 mutation analysis in reclassified cases supported the validity of the reclassification. Two major molecular subgroups can be identified in the remaining PTCL-NOS cases characterized by high expression of either GATA3 (33%; 40/121) or TBX21 (49%; 59/121). The GATA3 subgroup was significantly associated with poor overall survival (P = .01). High expression of cytotoxic gene-signature within the TBX21 subgroup also showed poor clinical outcome (P = .05). In AITL, high expression of several signatures associated with the tumor microenvironment was significantly associated with outcome. A combined prognostic score was predictive of survival in an independent cohort (P = .004).

Unifying niche shift studies: insights from biological invasions.

Assessing whether the climatic niche of a species may change between different geographic areas or time periods has become increasingly important in the context of ongoing global change. However, approaches and findings have remained largely controversial so far, calling for a unification of methods. Here, we build on a review of empirical studies of invasion to formalize a unifying framework that decomposes niche change into unfilling, stability, and expansion situations, taking both a pooled range and range-specific perspective on the niche, while accounting for climatic availability and climatic analogy. This framework provides new insights into the nature of climate niche shifts and our ability to anticipate invasions, and may help in guiding the design of experiments for assessing causes of niche changes.

Chemical properties of soils treated with biological sludge from gelatin industry

The impact of agro-industrial organic wastes in the environment can be reduced when used in agriculture. From the standpoint of soil fertility, residue applications can increase the organic matter content and provide nutrients for plants. This study evaluated the effect of biological sludge from gelatin industry on the chemical properties of two Ultisols (loamy sand and sandy clay) and an Oxisol (clay). The experiment lasted 120 days and was carried out in laboratory in a completely randomized design with factorial arrangement, combining the three soils and six biological sludge rates (0, 100, 200, 300, 400, and 500 m³ ha-1), with three replications. Biological sludge rates of up to 500 m³ ha-1 decreased soil acidity and increased the effective cation exchange capacity (CEC) and N, Ca, Mg, and P availability, without exceeding the tolerance limit for Na. The increase in exchangeable base content, greater than the effective CEC, indicates that the major part of cations added by the sludge remains in solution and can be lost by leaching.