Spatio-temporal variability of sugarcane yield efficiency in the state of São Paulo, Brazil

The objective of this work was to assess the spatial and temporal variability of sugarcane yield efficiency and yield gap in the state of São Paulo, Brazil, throughout 16 growing seasons, considering climate and soil as main effects, and socioeconomic factors as complementary. An empirical model was used to assess potential and attainable yields, using climate data series from 37 weather stations. Soil effects were analyzed using the concept of production environments associated with a soil aptitude map for sugarcane. Crop yield efficiency increased from 0.42 to 0.58 in the analyzed period (1990/1991 to 2005/2006 crop seasons), and yield gap consequently decreased from 58 to 42%. Climatic factors explained 43% of the variability of sugarcane yield efficiency, in the following order of importance: solar radiation, water deficit, maximum air temperature, precipitation, and minimum air temperature. Soil explained 15% of the variability, considering the average of all seasons. There was a change in the correlation pattern of climate and soil with yield efficiency after the 2001/2002 season, probably due to the crop expansion to the west of the state during the subsequent period. Socioeconomic, biotic and crop management factors together explain 42% of sugarcane yield efficiency in the state of São Paulo.

Stronger transferability but lower variability in transcriptomic- than in anonymous microsatellites: evidence from Hylid frogs.

A simple way to quickly optimize microsatellites in nonmodel organisms is to reuse loci available in closely related taxa; however, this approach can be limited by the stochastic and low cross-amplification success experienced in some groups (e.g. amphibians). An efficient alternative is to develop loci from transcriptome sequences. Transcriptomic microsatellites have been found to vary in their levels of cross-species amplification and variability, but this has to date never been tested in amphibians. Here, we compare the patterns of cross-amplification and levels of polymorphism of 18 published anonymous microsatellites isolated from genomic DNA vs. 17 loci derived from a transcriptome, across nine species of tree frogs (Hyla arborea and Hyla cinerea group). We established a clear negative relationship between divergence time and amplification success, which was much steeper for anonymous than transcriptomic markers, with half-lives (time at which 50% of the markers still amplify) of 1.1 and 37 My, respectively. Transcriptomic markers are significantly less polymorphic than anonymous loci, but remain variable across diverged taxa. We conclude that the exploitation of amphibian transcriptomes for developing microsatellites seems an optimal approach for multispecies surveys (e.g. analyses of hybrid zones, comparative linkage mapping), whereas anonymous microsatellites may be more informative for fine-scale analyses of intraspecific variation. Moreover, our results confirm the pattern that microsatellite cross-amplification is greatly variable among amphibians and should be assessed independently within target lineages. Finally, we provide a bank of microsatellites for Palaearctic tree frogs (so far only available for H. arborea), which will be useful for conservation and evolutionary studies in this radiation.

Forecasting the Earth"s radiation belts and modeling solar energetic particle events: Recent results from SPACECAST

High-energy charged particles in the van Allen radiation belts and in solar energetic particle events can damage satellites on orbit leading to malfunctions and loss of satellite service. Here we describe some recent results from the SPACECAST project on modelling and forecasting the radiation belts, and modelling solar energetic particle events. We describe the SPACECAST forecasting system that uses physical models that include wave-particle interactions to forecast the electron radiation belts up to 3 h ahead. We show that the forecasts were able to reproduce the >2 MeV electron flux at GOES 13 during the moderate storm of 7-8 October 2012, and the period following a fast solar wind stream on 25-26 October 2012 to within a factor of 5 or so. At lower energies of 10- a few 100 keV we show that the electron flux at geostationary orbit depends sensitively on the high-energy tail of the source distribution near 10 RE on the nightside of the Earth, and that the source is best represented by a kappa distribution. We present a new model of whistler mode chorus determined from multiple satellite measurements which shows that the effects of wave-particle interactions beyond geostationary orbit are likely to be very significant. We also present radial diffusion coefficients calculated from satellite data at geostationary orbit which vary with Kp by over four orders of magnitude. We describe a new automated method to determine the position at the shock that is magnetically connected to the Earth for modelling solar energetic particle events and which takes into account entropy, and predict the form of the mean free path in the foreshock, and particle injection efficiency at the shock from analytical theory which can be tested in simulations.

Genetic variability of rice recurrent selection populations as affected by male sterility or manual recombination

The objective of this work was to determine the effect of male sterility or manual recombination on genetic variability of rice recurrent selection populations. The populations CNA-IRAT 4, with a gene for male sterility, and CNA 12, which was manually recombined, were evaluated. Genetic variability among selection cycles was estimated using14 simple sequence repeat (SSR) markers. A total of 926 plants were analyzed, including ten genitors and 180 individuals from each of the evaluated cycles (1, 2 and 5) of the population CNA-IRAT 4, and 16 genitors and 180 individuals from each of the cycles (1 and 2) of CNA 12. The analysis allowed the identification of alleles not present among the genitors for both populations, in all cycles, especially for the CNA-IRAT 4 population. These alleles resulted from unwanted fertilization with genotypes that were not originally part of the populations. The parameters of Wright's F-statistic (F IS and F IT) indicated that the manual recombination expands the genetic variability of the CNA 12 population, whereas male sterility reduces the one of CNA-IRAT 4.

Recombination is suppressed and variability reduced in a nascent Y chromosome.

Several hypotheses have been elaborated to account for the evolutionary decay commonly observed in full-fledged Y chromosomes. Enhanced drift, background selection and selective sweeps, which are expected to result from reduced recombination, may all share responsibilities in the initial decay of proto-Y chromosomes, but little empirical information has been gathered so far. Here we take advantage of three markers that amplify on both of the morphologically undifferentiated sex chromosomes of the European tree frog (Hyla arborea) to show that recombination is suppressed in males (the heterogametic sex) but not in females. Accordingly, genetic variability is reduced on the Y, but in a way that can be accounted for by merely the number of chromosome copies per breeding pair, without the need to invoke background selection or selective sweeps.

Unexpected genomic variability in clinical and environmental strains of the pathogenic yeast Candida parapsilosis

Invasive candidiasis is the most commonly reported invasive fungal infection worldwide. Although Candida albicans remains the main cause, the incidence of emerging Candida species, such as C. parapsilosis is increasing. It has been postulated that C. parapsilosis clinical isolates result from a recent global expansion of a virulent clone. However, the availability of a single genome for this species has so far prevented testing this hypothesis at genomic scales. We present here the sequence of three additional strains from clinical and environmental samples. Our analyses reveal unexpected patterns of genomic variation, shared among distant strains, that argue against the clonal expansion hypothesis. All strains carry independent expansions involving an arsenite transporter homolog, pointing to the existence of directional selection in the environment, and independent origins of the two clinical isolates. Furthermore, we report the first evidence for the existence of recombination in this species. Altogether, our results shed new light onto the dynamics of genome evolution in C. parapsilosis.

ADME pharmacogenetics: investigation of the pharmacokinetics of the antiretroviral agent lopinavir coformulated with ritonavir.

BACKGROUND: An ADME (absorption, distribution, metabolism and excretion)-pharmacogenetics association study may identify functional variants relevant to the pharmacokinetics of lopinavir co-formulated with ritonavir (LPV/r), a first-line anti-HIV agent. METHODS: An extensive search of literature and web resources helped select ADME genes and single nucleotide polymorphisms (SNPs, functional and HapMap tagging SNPs) with a proven or potentially relevant role in LPV/r pharmacokinetics. The study followed a two-stage design. Stage 1 (discovery) considered a Caucasian population (n=638) receiving LPV/r, where we selected 117 individuals with low LPV clearance (cases) and 90 individuals with high clearance (controls). Genotyping was performed by a 1536-SNP customized GoldenGate Illumina BeadArray. Stage 2 (confirmation) represented a replication study of candidate SNPs from the stage 1 in 148 individuals receiving LPV/r. The analysis led to formal population pharmacokinetic-pharmacogenetic modeling of demographic, environmental and candidate SNP effects. RESULTS: One thousand three hundred and eighty SNPs were successfully genotyped. Nine SNPs prioritized by the stage 1 analysis were brought to replication. Stage 2 confirmed the contribution of two functional SNPs in SLCO1B1, one functional SNP in ABCC2 and a tag SNP of the CYP3A locus in addition to body weight effect and ritonavir coadministration. According to the population pharmacokinetic-pharmacogenetic model, genetic variants explained 5% of LPV variability. Individuals homozygous rs11045819 (SLCO1B1*4) had a clearance of 12.6 l/h, compared with 5.4 l/h in the reference group, and 3.9 l/h in individuals with two or more variant alleles of rs4149056 (SLCO1B1*5), rs717620 (ABCC2) or rs6945984 (CYP3A). A subanalysis confirmed that although a significant part of the variance in LPV clearance was attributed to fluctuation in ritonavir levels, genetic variants had an additional effect on LPV clearance. CONCLUSION: The two-stage strategy successfully identified genetic variants affecting LPV/r pharmacokinetics. Such a general approach of ADME pharmacogenetics should be generalized to other drugs.

Modeling and mitigation of supply-demand mismatches

In this thesis, I develop analytical models to price the value of supply chain investments under demand uncer¬tainty. This thesis includes three self-contained papers. In the first paper, we investigate the value of lead-time reduction under the risk of sudden and abnormal changes in demand forecasts. We first consider the risk of a complete and permanent loss of demand. We then provide a more general jump-diffusion model, where we add a compound Poisson process to a constant-volatility demand process to explore the impact of sudden changes in demand forecasts on the value of lead-time reduction. We use an Edgeworth series expansion to divide the lead-time cost into that arising from constant instantaneous volatility, and that arising from the risk of jumps. We show that the value of lead-time reduction increases substantially in the intensity and/or the magnitude of jumps. In the second paper, we analyze the value of quantity flexibility in the presence of supply-chain dis- intermediation problems. We use the multiplicative martingale model and the "contracts as reference points" theory to capture both positive and negative effects of quantity flexibility for the downstream level in a supply chain. We show that lead-time reduction reduces both supply-chain disintermediation problems and supply- demand mismatches. We furthermore analyze the impact of the supplier's cost structure on the profitability of quantity-flexibility contracts. When the supplier's initial investment cost is relatively low, supply-chain disin¬termediation risk becomes less important, and hence the contract becomes more profitable for the retailer. We also find that the supply-chain efficiency increases substantially with the supplier's ability to disintermediate the chain when the initial investment cost is relatively high. In the third paper, we investigate the value of dual sourcing for the products with heavy-tailed demand distributions. We apply extreme-value theory and analyze the effects of tail heaviness of demand distribution on the optimal dual-sourcing strategy. We find that the effects of tail heaviness depend on the characteristics of demand and profit parameters. When both the profit margin of the product and the cost differential between the suppliers are relatively high, it is optimal to buffer the mismatch risk by increasing both the inventory level and the responsive capacity as demand uncertainty increases. In that case, however, both the optimal inventory level and the optimal responsive capacity decrease as the tail of demand becomes heavier. When the profit margin of the product is relatively high, and the cost differential between the suppliers is relatively low, it is optimal to buffer the mismatch risk by increasing the responsive capacity and reducing the inventory level as the demand uncertainty increases. In that case, how¬ever, it is optimal to buffer with more inventory and less capacity as the tail of demand becomes heavier. We also show that the optimal responsive capacity is higher for the products with heavier tails when the fill rate is extremely high.

Implicit methods for qualitative modeling of gene regulatory networks.

Advancements in high-throughput technologies to measure increasingly complex biological phenomena at the genomic level are rapidly changing the face of biological research from the single-gene single-protein experimental approach to studying the behavior of a gene in the context of the entire genome (and proteome). This shift in research methodologies has resulted in a new field of network biology that deals with modeling cellular behavior in terms of network structures such as signaling pathways and gene regulatory networks. In these networks, different biological entities such as genes, proteins, and metabolites interact with each other, giving rise to a dynamical system. Even though there exists a mature field of dynamical systems theory to model such network structures, some technical challenges are unique to biology such as the inability to measure precise kinetic information on gene-gene or gene-protein interactions and the need to model increasingly large networks comprising thousands of nodes. These challenges have renewed interest in developing new computational techniques for modeling complex biological systems. This chapter presents a modeling framework based on Boolean algebra and finite-state machines that are reminiscent of the approach used for digital circuit synthesis and simulation in the field of very-large-scale integration (VLSI). The proposed formalism enables a common mathematical framework to develop computational techniques for modeling different aspects of the regulatory networks such as steady-state behavior, stochasticity, and gene perturbation experiments.

Simulating maize yield in sub‑tropical conditions of southern Brazil using Glam model

The objective of this work was to evaluate the feasibility of simulating maize yield in a sub‑tropical region of southern Brazil using the general large area model (Glam). A 16‑year time series of daily weather data were used. The model was adjusted and tested as an alternative for simulating maize yield at small and large spatial scales. Simulated and observed grain yields were highly correlated (r above 0.8; p<0.01) at large scales (greater than 100,000 km²), with variable and mostly lower correlations (r from 0.65 to 0.87; p<0.1) at small spatial scales (lower than 10,000 km²). Large area models can contribute to monitoring or forecasting regional patterns of variability in maize production in the region, providing a basis for agricultural decision making, and Glam‑Maize is one of the alternatives.

JPEG standard uniform quantization error modeling with applications to sequential and progressive operation modes

In this paper we propose a method for computing JPEG quantization matrices for a given mean square error or PSNR. Then, we employ our method to compute JPEG standard progressive operation mode definition scripts using a quantization approach. Therefore, it is no longer necessary to use a trial and error procedure to obtain a desired PSNR and/or definition script, reducing cost. Firstly, we establish a relationship between a Laplacian source and its uniform quantization error. We apply this model to the coefficients obtained in the discrete cosine transform stage of the JPEG standard. Then, an image may be compressed using the JPEG standard under a global MSE (or PSNR) constraint and a set of local constraints determined by the JPEG standard and visual criteria. Secondly, we study the JPEG standard progressive operation mode from a quantization based approach. A relationship between the measured image quality at a given stage of the coding process and a quantization matrix is found. Thus, the definition script construction problem can be reduced to a quantization problem. Simulations show that our method generates better quantization matrices than the classical method based on scaling the JPEG default quantization matrix. The estimation of PSNR has usually an error smaller than 1 dB. This figure decreases for high PSNR values. Definition scripts may be generated avoiding an excessive number of stages and removing small stages that do not contribute during the decoding process with a noticeable image quality improvement.

Genetic variability of marine shrimp in the Brazilian industry

The objective of this work was to estimate the genetic variability level and distribution in Brazilian broodstocks of marine shrimp (Litopenaeus vannamei). Nine of the country's largest hatcheries were evaluated using codominant and highly polymorphic microsatellite markers. The results obtained from genotyping of ten microsatellite loci are indicative of genetic variability that is compatible with that found in wild populations of L. vannamei in Mexico and Central America. A possible explanation is the highly diversified and relatively recent origin of the available broodstocks. Bayesian analysis detected a signal for five founding populations. The distribution of genetic distances partially reflects geographical location, and this information will be useful for the creation of new broodstocks. Therefore, L. vannamei genetic variability among nine of the largest national hatcheries can be considered high.

Mitochondrial control region and microsatellite data show low genetic variability in reared senegalese sole, Solea senegalensis. Preliminary data

Peer reviewed

Controls on 13C and 14C variability in soil CO2

14C dating of groundwater depends on the isotopic composition of both the solid carbonate and the soil CO2 and requires the use of 14C age correction models. To better assess the variability of the 14C activity of soil CO2 (A14Csoil-CO2) and the δ13C of soil CO2 (δ13Csoil-CO2), which are two parameters used in 14C age correction models, we studied the different processes involving carbon isotopes in the soil. The approach used experimental data from two sites in France (Fontainebleau sands and Astian sands) and a steady-state transport model. In most cases, the 14C activity (A14C) of atmospheric CO2 is directly used in the 14C age correction models as the A14Csoil-CO2. However, we demonstrate that since 1950, the evolution of the A14Csoil-CO2 reflects the competition between the fluxes of root-derived CO2 and organic matter-derived CO2. Therefore, the A14Csoil-CO2 must be used to date groundwater that is younger than 60 years old. Moreover, the δ13C of soil CO2 (δ13Csoil-CO2) showed large seasonal variations that must be taken into account in selecting the δ13Csoil-CO2 for 14C age correction models.