Peanut mechanized digging regarding to plant population and soil water level

The largest losses in mechanical harvesting of peanuts occur during the stage of digging, and its assessment is still incipient in Brazil. Therefore, the aim of this study was to evaluate the quantitative losses and the performance of the tractor-digger-inverter, according to soil water content and plant populations. The experiment was conducted in a completely randomized block design with a factorial scheme 2 x 3, in which the treatments consisted of two soil, water content (19.3 and 24.8%) and three populations of plants (86,111, 127,603 and 141,144 plants ha-1), with four replications. The quantitative digging losses and the set mechanized performance were evaluated. The largest amount of visible and total losses was found in the population of 141.144 plants ha-1 for the 19.3% soil water content. The harvested material flow and the tractor-digger-inverter performance were not influenced by soil water content and plant population. The water content in the pods was higher in 24.8% soil water content only for the population of 86,111 plants ha-1; the yield was higher in the populations of 141.144 and 127.603 plants ha-1, in the 19.3 e 24.8% soil water content, respectively.

Distribution of Brazilian dermatologists according to geographic location, population and HDI of municipalities: an ecological study

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Paradoxical effects of bovine somatotropin treatment on the ovarian follicular population and in vitro embryo production of lactating buffalo donors submitted to ovum pick-up

The aim of the present study was to evaluate the effect of bovine somatotropin (bST; 500 mg) administration on lactating buffalo donors submitted to two different ovum pick-up (OPU) and in vitro embryo production schemes with a 7 or 14 d intersession OPU interval. A total of 16 lactating buffalo cows were randomly assigned into one of four experimental groups according to the bST treatment (bST or No-bST) and the OPU intersession interval (7 or 14 d) in a 2 x 2 factorial design (16 weeks of OPU sessions). The females submitted to OPU every 14d had a larger (P < 0.001) number of ovarian follicles suitable for puncture (15.6 +/- 0.7 vs. 12.8 +/- 0.4) and an increased (P = 0.004) number of cumulus-oocyte complexes (COCs) recovered (10.0 +/- 0.5 vs. 8.5 +/- 0.3) compared to the 7 d interval group. However, a 7 or 14 d interval between OPU sessions had no effect (P = 0.34) on the number of blastocysts produced per OPU (1.0 +/- 0.1 vs. 13 +/- 0.2, respectively). In addition, bST treatment increased (P < 0.001) the number of ovarian follicles suitable for puncture (15.3 +/- 0.5 vs. 12.1 +/- 0.4) but reduced the percentage (18.9% vs. 10.9%; P = 0.009) and the number (1.4 +/- 0.2 vs. 0.8 +/- 0.1; P = 0.003) of blastocysts produced per OPU session compared with the non-bST-treated buffaloes. In conclusion, the 14d interval between OPU sessions and bST treatment efficiently increased the number of ovarian follicles suitable for puncture. However, the OPU session interval had no effect on embryo production, and bST treatment reduced the in vitro blastocyst outcomes in lactating buffalo donors.

EC90-732 Sugarbeet Population and Spacing Calculator

This extension circular is a slide rule used to help a producer calculate the row spacing, seed population, and estimated percentage of emergence of sugarbeet. A producer can also use this slide rule to find the plant population from plants/100 feet of row at 22" and 30" row spacings.

Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.

MORTALITY IN THE MEDICARE POPULATION AND CHRONIC EXPOSURE TO FINE PARTICULATE AIR POLLUTION

Prospective cohort studies have provided evidence on longer-term mortality risks of fine particulate matter (PM2.5), but due to their complexity and costs, only a few have been conducted. By linking monitoring data to the U.S. Medicare system by county of residence, we developed a retrospective cohort study, the Medicare Air Pollution Cohort Study (MCAPS), comprising over 20 million enrollees in the 250 largest counties during 2000-2002. We estimated log-linear regression models having as outcome the age-specific mortality rate for each county and as the main predictor, the average level for the study period 2000. Area-level covariates were used to adjust for socio-economic status and smoking. We reported results under several degrees of adjustment for spatial confounding and with stratification into by eastern, central and western counties. We estimated that a 10 µg/m3 increase in PM25 is associated with a 7.6% increase in mortality (95% CI: 4.4 to 10.8%). We found a stronger association in the eastern counties than nationally, with no evidence of an association in western counties. When adjusted for spatial confounding, the estimated log-relative risks drop by 50%. We demonstrated the feasibility of using Medicare data to establish cohorts for follow-up for effects of air pollution. Particulate matter (PM) air pollution is a global public health problem (1). In developing countries, levels of airborne particles still reach concentrations at which serious health consequences are well-documented; in developed countries, recent epidemiologic evidence shows continued adverse effects, even though particle levels have declined in the last two decades (2-6). Increased mortality associated with higher levels of PM air pollution has been of particular concern, giving an imperative for stronger protective regulations (7). Evidence on PM and health comes from studies of acute and chronic adverse effects (6). The London Fog of 1952 provides dramatic evidence of the unacceptable short-term risk of extremely high levels of PM air pollution (8-10); multi-site time-series studies of daily mortality show that far lower levels of particles are still associated with short-term risk (5)(11-13). Cohort studies provide complementary evidence on the longer-term risks of PM air pollution, indicating the extent to which exposure reduces life expectancy. The design of these studies involves follow-up of cohorts for mortality over periods of years to decades and an assessment of mortality risk in association with estimated long-term exposure to air pollution (2-4;14-17). Because of the complexity and costs of such studies, only a small number have been conducted. The most rigorously executed, including the Harvard Six Cities Study and the American Cancer Society’s (ACS) Cancer Prevention Study II, have provided generally consistent evidence for an association of long- term exposure to particulate matter air pollution with increased all-cause and cardio-respiratory mortality (2,4,14,15). Results from these studies have been used in risk assessments conducted for setting the U.S. National Ambient Air Quality Standard (NAAQS) for PM and for estimating the global burden of disease attributable to air pollution (18,19). Additional prospective cohort studies are necessary, however, to confirm associations between long-term exposure to PM and mortality, to broaden the populations studied, and to refine estimates by regions across which particle composition varies. Toward this end, we have used data from the U.S. Medicare system, which covers nearly all persons 65 years of age and older in the United States. We linked Medicare mortality data to (particulate matter less than 2.5 µm in aerodynamic diameter) air pollution monitoring data to create a new retrospective cohort study, the Medicare Air Pollution Cohort Study (MCAPS), consisting of 20 million persons from 250 counties and representing about 50% of the US population of elderly living in urban settings. In this paper, we report on the relationship between longer-term exposure to PM2.5 and mortality risk over the period 2000 to 2002 in the MCAPS.

Population and molecular evolution studies on the Melanocortin 1 receptor locus implicate its role in human pigmentation variation

Human pigmentation is a complex trait with the observed variation caused by the varied production of eumelanin (brown/black melanins) and phaeomelanin (red/yellow melanins) by the melanocytes. The melanocortin 1 receptor (MC1R), a G protein-coupled receptor expressed in the melanocytes, is a regulator eu- and phaeomelanin synthesis, and MC1R mutations causing skin and coat color changes are known in many mammals. To understand the role of MC1R in human pigmentation variation, I have sequenced the MC1R gene in 121 individuals sampled from world populations. In addition, I have sequenced the MC1R gene in common and pygmy chimpanzees, gorilla, orangutan, and baboon to study the evolution of MC1R and to infer the ancestral human MC1R sequence. The ancestral MC1R sequence is observed in all 25 African individuals studied, but at lower frequencies in the other populations examined, especially in East and Southeast Asians. The Arg163Gln variant is absent in the Africans studied, almost absent in Europeans, and at a low frequency in Indians, but is at an exceptionally high frequency (70%) in East and Southeast Asians. To further evaluate the role of MC1R variants in human pigmentation variation, I have combined these molecular evolution and population studies with functional assays on MC1R variants and primate MC1Rs. ^

14C Analysis and Sample Preparation at the New Bern Laboratory for the Analysis of Radiocarbon with AMS (LARA)

The University of Bern has set up the new Laboratory for the Analysis of Radiocarbon with AMS (LARA) equipped with an accelerator mass spectrometer (AMS) MICADAS (MIni CArbon Dating System) to continue its long history of 14C analysis based on conventional counting. The new laboratory is designated to provide routine 14C dating for archaeology, climate research, and other disciplines at the University of Bern and to develop new analytical systems coupled to the gas ion source for 14C analysis of specific compounds or compound classes with specific physical properties. Measurements of reference standards and wood samples dated by dendrochronology demonstrate the quality of the 14C analyses performed at the new laboratory.

Infra-Population and -Community Dynamics of the Parasites Nosema apis and Nosema ceranae, and Consequences for Honey Bee (Apis mellifera) Hosts

Nosema spp. fungal gut parasites are among myriad possible explanations for contemporary increased mortality of western honey bees (Apis mellifera, hereafter honey bee) in many regions of the world. Invasive Nosema ceranae is particularly worrisome because some evidence suggests it has greater virulence than its congener N. apis. N. ceranae appears to have recently switched hosts from Asian honey bees (Apis cerana) and now has a nearly global distribution in honey bees, apparently displacing N. apis. We examined parasite reproduction and effects of N. apis, N. ceranae, and mixed Nosema infections on honey bee hosts in laboratory experiments. Both infection intensity and honey bee mortality were significantly greater for N. ceranae than for N. apis or mixed infections; mixed infection resulted in mortality similar to N. apis parasitism and reduced spore intensity, possibly due to inter-specific competition. This is the first long-term laboratory study to demonstrate lethal consequences of N. apis and N. ceranae and mixed Nosema parasitism in honey bees, and suggests that differences in reproduction and intra-host competition may explain apparent heterogeneous exclusion of the historic parasite by the invasive species