Compositional data analysis with Red-R

The compositional analyst must use a series of software to transform raw compositional data and run statistical analyses on them. Tools for compositional data analysis are available in R, an open source widely-used statistical computing environment. However, using R requires prior programming knowledge. Red-R is an open-source, user-friendly visual data flow interface based on R. The interface uses principles of pipeline programming where functions are represented as icons, termed widgets, and data flows from one function to another by drawing lines between them on a canvas. Red-R is able to perform common data analysis tasks (hypothesis tests, analysis of variance, regressions, principal component analysis, data cloud plots, bar plots, biplots, etc.). We have developed a novel Red-R package which implements the compositions package in R. Our compositions package can be used to perform compositional data operations over raw data (closure, additive, centered and isometric log ratio transformations, perturbations and powering, etc.), and create compositional plots (ternary diagrams, ilrdendrograms, etc.) without prior programming knowledge, after few basic operations. The objective of this work is to present Red-R and its compositions package using an application example for geochemical data. The network of widgets provides an easy-tofollow step-by-step procedure to run a large number of operations available in R, hence facilitating the tasks of the compositional data analyst. Furthermore, the entire analysis network can be saved and reloaded. Reports can be generated from the widget network to document and share results. Non-programmers can have an easy access to the advanced tools available in compositions analysis

Fractal and compositional analysis of soil aggregation

A soil aggregate is made of closely packed sand, silt, clay, and organic particles building up soil structure. Soil aggregation is a soil quality index integrating the chemical, physical, and biological processes involved in the genesis of soil structure and tilth. Aggregate size distribution is determined by sieving a fixed amount of soil mass under mechanical stress and is commonly synthesized by the mean weight diameter (MWD) and fractal dimensions such as the fragmentation fractal dimensions (D f). A fractal is a rough object that can be broken down into a number of reduced-size copies of the original object. Equations have been developed to compute bounded and unbounded scaling factors as measures of fractal dimensions based on assumptions about average diameter, bulk density, shape and probability of failure of sieved particles. The log-log relationship between particle diameter and cumulative number or mass of aggregates or soil particles above a given diameter often shows more or less uniform fractal patterns. Multi-fractal (slopes showing several D f values ≤ 3) and non fractal patterns or incomplete fragmentation ( D f 3) have been reported. Scaling factors are curve- fitting parameters that are very sensitive to the choice of the fractal domain about breakpoints. Compositional data analysis using sequential binary partitions for isometric log ratio (ilr) coordinates with orthonormal basis provides a novel approach that avoids the assumptions and dimensional constraints of fractal analysis. Our objective was to compare MWD, fractal scaling factors and ilr coordinates using published data. In the first dataset, MWD was found to be biased by excessively high weight being given to the largest aggregate-size. Eight ilr coordinates contrasting micro- vs. macro-aggregates were related to fragmentation fractal dimensions, most of which were below 2 or above 3, a theoretical impossibility for geometric fractals. The critical ilr value separating scaling factors 3 and > 3 was close to zero. In a second dataset, the Aitchison distance computed across ilr coordinates proved to be a useful measure of the degree of soil aggregation, agradation or degradation against a reference composition such as that of primary particles, bare fallow or permanent grass. The individual contributions of ilr coordinates to the Aitchison distance can be interpreted in terms of sign and amplitude and be related to soil properties and processes mediated by soil aggregation

Self-Assembly of Polyhedral Hybrid Colloidal Particles

We have developed a new method to produce hybrid particles with polyhedral shapes in very high yield (liter quantities at up to 70% purity) using a combination of emulsion polymerization and inorganic surface chemistry. The procedure has been generalized to create complex geometries, including hybrid line segments, triangles, tetrahedra, octahedra, and more. The optical properties of these particles are tailored for studying their dynamics and self-assembly. For example, we produce systems that consist of index-matched spheres allowing us to define the position of each elementary particle in three-dimensional space. We present some preliminary studies on the self-assembly of these complex shaped systems based on electron and optical microscopy.Engineering and Applied SciencesPhysic

Compositional meta-analysis of citrus varieties in the state of São Paulo, Brazil

Brazil is the largest orange (Citrus sinensis) producer worldwide. The nutrient management of orange orchards is designed from experiments on a limited number of varieties. This knowledge is transferred to other varieties by diagnosing tissue nutrient composition. Nutrient diagnostic tools are based on nutrient concentration (critical minimum value or CMV) and ratio (Diagnosis and Recommendation Integrated System or DRIS) norms that disregard the compositional nature of analytical data and the limited number of nutrient ratios that can be diagnosed independently in a given composition. The diagnosis of cationic micronutrients is also biased by contamination from fungicides. Compositional data analysis that can avoid such problems has been first applied to tissue analysis of agricultural crops using centered log ratios (Compositional Nutrient Diagnosis – CND-clr). The isometric log ratio (ilr) transformation is a new approach based on binary nutrient ratios and the principle of orthogonality (CND-ilr). Binary partitions can be defined and varietal nutrient profiles classified based on positive and negative nutrient interactions and meta-analysis. We analyzed 11 nutrients (N, S, P, K, Ca, Mg, B, Cu, Zn, Mn, Fe) in tissue samples across 108 orchard areas, i.e. 31 ‘Valencia’, 22 ‘Hamlin’, 20 ‘Pêra’, and 35 ‘Natal’. Nutrients were partitioned between macro- and micro-nutrients as well as anionic and cationic species. The effect size of varieties over ‘Valencia’ was quantified by the mean and standard deviation of ilr values across ilr coordinates. Specific varietal nutrient profiles and ilr norms were defined. To guide correcting nutrient deficiencies by appropriate nutrient management, compositions can be varied by a perturbation vector on nutrients with to the largest and most negative influence on ilr differences from ilr norms until the Aitchison distance falls below critical value

Quonops©, la prévision opérationnelle en acoustique sous-marine sur grille de calcul

National audienceQuonops©, la prévision opérationnelle en acoustique sous-marine sur grille de calcu

Quonops©, la prévision opérationnelle en acoustique sous-marine sur grille de calcul

National audienceQuonops©, la prévision opérationnelle en acoustique sous-marine sur grille de calcu

Impact of fertilization on the firmness of cranberry (Vaccinium macrocarpon AIT.)

Abstract. Québec is one of the leading cranberry (Vaccinium macrocarpon Ait.) or called ‘Atoka’ in the Iroquoian language, producers in the world. Fertilization is a key management tool to reach high fruit yield and good quality. For example, in blueberries, rates and application methods of fertilizers can affect fruit firmness. N showed the greatest effect on the development, flowering, and productivity of the cranberry plant. On the other side, hand harvesting is preferred for marketing of fresh fruit since the physical abuse of mechanical harvesting reduces fruit firmness and substantially reduces market life. The objective of this research was to study the potential of firmness reflectance TA.TX2 Texture Analyzer as a means for measurement of fresh fruit firmness. Four experimental sites were established since 2014 on podzolic acid sandy soils containing more than 90% sand at Notre Dame-de-Lourdes and St-Louis-de-Blandford in central Québec. The experimental design was a randomized complete block with cv. “Stevens” established on permanent plots comprised five N, three P, four K and S, and also two Mg, Cu and B doses. Berries were hand-harvested on 0.37 m2 areas, 2-3 weeks before commercial harvesting. The fruits from zero N treatment were best for firmness and economic profit. Although, These N application rates discourage a good relationship between commercial yield and fruit quality. In other hand, the zero N rate resulted in lowest yield production and high quality; the fruit had the greatest N (60 kg ha-1) rate was diminished significantly firmness of the cranberry fruit. Finally, the 45 kg N ha-1 rate produced high yield with the buildup and maintenance concept and poor fruit quality

The Formation and Stability of Recognition Memory: What Happens Upon Recall?

The idea that an already consolidated memory can become destabilized after recall and requires a process of reconsolidation to maintain it for subsequent use has gained much credence over the past decade. Experimental studies in rodents have shown pharmacological, genetic, or injurious manipulation at the time of memory reactivation can disrupt the already consolidated memory. Despite the force of experimental data showing this phenomenon, a number of questions have remained unanswered and no consensus has emerged as to the conditions under which a memory can be disrupted following reactivation. To date most rodent studies of reconsolidation are based on negatively reinforced memories, in particular fear-associated memories, while the storage and stability of forms of memory that do not rely on explicit reinforcement have been less often studied. In this review, we focus on recognition memory, a paradigm widely used in humans to probe declarative memory. We briefly outline recent advances in our understanding of the processes and brain circuits involved in recognition memory and review the evidence that recognition memory can undergo reconsolidation upon reactivation. We also review recent findings suggesting that some molecular mechanisms underlying consolidation of recognition memory are similarly recruited after recall to ensure memory stability, while others are more specifically engaged in consolidation or reconsolidation. Finally, we provide novel data on the role of Rsk2, a mental retardation gene, and of the transcription factor zif268/egr1 in reconsolidation of object-location memory, and offer suggestions as to how assessing the activation of certain molecular mechanisms following recall in recognition memory may help understand the relative importance of different aspects of remodeling or updating long-lasting memories

Design and verification of the Far Ultraviolet Spectrographic Imager (FUV-SI) for the IMAGE mission

peer reviewedThe IMAGE FUV-SI is simultaneously imaging auroras at 121.8 nm and 135.8 nm. The spectrograph design challenge is the efficient rejection of the intense Lyman-alpha emission at 121.6 nm while passing its Doppler-shifted component at 121.8 nm. The FUV-SI opto-mechanical design, analysis integration, and verification of performances against environment are discussed in this paper. In absence of STM environmental constraints at subsystem levels are derived analytically from F.E.M. and used for pre-qualifying optical subsystems