Earthworms from Mato Grosso, Brazil, and new records of species from the state

The objective of this work was to undertake a qualitative assessment of earthworm diversity in areas under human influence, in a region of Cerrado-Pantanal-Amazon rainforest transition, in the state of Mato Grosso, Brazil. The earthworms were collected in the municipalities of Barra do Bugres and Arenápolis, and were studied together with species previously identified from other municipalities. Seventeen municipalities, at 29 sampling points of Mato Grosso State, have been sampled. Seven species of earthworms were collected and identified in Barra do Bugres: Goiascolex vanzolinii, Pontoscolex (Pontoscolex) corethrurus, Opisthodrillus borellii borellii, Opisthodrillus sp., Dichogaster (Diplothecodrilus) gracilis, Dichogaster sp. and a species of the Criodrilidae family. Four species of earthworms were identified in Arenápolis: Pontoscolex (Pontoscolex) corethrurus, Dichogaster (Diplothecodrilus) gracilis, Dichogaster (Diplothecodrilus) affinis and Dichogaster sp. In total, 32 earthworm species/subspecies are known from Mato Grosso, 22 native and 10 exotic.

Assessment of cytomegalovirus-specific cell-mediated immunity for the prediction of cytomegalovirus disease in high-risk solid-organ transplant recipients: a multicenter cohort study.

BACKGROUND: Cytomegalovirus (CMV) disease remains an important problem in solid-organ transplant recipients, with the greatest risk among donor CMV-seropositive, recipient-seronegative (D(+)/R(-)) patients. CMV-specific cell-mediated immunity may be able to predict which patients will develop CMV disease. METHODS: We prospectively included D(+)/R(-) patients who received antiviral prophylaxis. We used the Quantiferon-CMV assay to measure interferon-γ levels following in vitro stimulation with CMV antigens. The test was performed at the end of prophylaxis and 1 and 2 months later. The primary outcome was the incidence of CMV disease at 12 months after transplant. We calculated positive and negative predictive values of the assay for protection from CMV disease. RESULTS: Overall, 28 of 127 (22%) patients developed CMV disease. Of 124 evaluable patients, 31 (25%) had a positive result, 81 (65.3%) had a negative result, and 12 (9.7%) had an indeterminate result (negative mitogen and CMV antigen) with the Quantiferon-CMV assay. At 12 months, patients with a positive result had a subsequent lower incidence of CMV disease than patients with a negative and an indeterminate result (6.4% vs 22.2% vs 58.3%, respectively; P < .001). Positive and negative predictive values of the assay for protection from CMV disease were 0.90 (95% confidence interval [CI], .74-.98) and 0.27 (95% CI, .18-.37), respectively. CONCLUSIONS: This assay may be useful to predict if patients are at low, intermediate, or high risk for the development of subsequent CMV disease after prophylaxis. CLINICAL TRIALS REGISTRATION: NCT00817908.

The Prediction of Creep and Shrinkage Properties of Concrete, HR-136, 1970

This report is concerned with the prediction of the long-time creep and shrinkage behavior of concrete. It is divided into three main areas. l. The development of general prediction methods that can be used by a design engineer when specific experimental data are not available. 2. The development of prediction methods based on experimental data. These methods take advantage of equations developed in item l, and can be used to accurately predict creep and shrinkage after only 28 days of data collection. 3. Experimental verification of items l and 2, and the development of specific prediction equations for four sand-lightweight aggregate concretes tested in the experimental program. The general prediction equations and methods are developed in Chapter II. Standard Equations to estimate the creep of normal weight concrete (Eq. 9), sand-lightweight concrete (Eq. 12), and lightweight concrete (Eq. 15) are recommended. These equations are developed for standard conditions (see Sec. 2. 1) and correction factors required to convert creep coefficients obtained from equations 9, 12, and 15 to valid predictions for other conditions are given in Equations 17 through 23. The correction factors are shown graphically in Figs. 6 through 13. Similar equations and methods are developed for the prediction of the shrinkage of moist cured normal weight concrete (Eq. 30}, moist cured sand-lightweight concrete (Eq. 33}, and moist cured lightweight concrete (Eq. 36). For steam cured concrete the equations are Eq. 42 for normal weight concrete, and Eq. 45 for lightweight concrete. Correction factors are given in Equations 47 through 52 and Figs., 18 through 24. Chapter III summarizes and illustrates, by examples, the prediction methods developed in Chapter II. Chapters IV and V describe an experimental program in which specific prediction equations are developed for concretes made with Haydite manufactured by Hydraulic Press Brick Co. (Eqs. 53 and 54}, Haydite manufactured by Buildex Inc. (Eqs. 55 and 56), Haydite manufactured by The Cater-Waters Corp. (Eqs. 57 and 58}, and Idealite manufactured by Idealite Co. (Eqs. 59 and 60). General prediction equations are also developed from the data obtained in the experimental program (Eqs. 61 and 62) and are compared to similar equations developed in Chapter II. Creep and Shrinkage prediction methods based on 28 day experimental data are developed in Chapter VI. The methods are verified by comparing predicted and measured values of the long-time creep and shrinkage of specimens tested at the University of Iowa (see Chapters IV and V) and elsewhere. The accuracy obtained is shown to be superior to other similar methods available to the design engineer.

Investigation of Rapid Thermal Analysis Procedures for Prediction of the Service Life of PCCP Carbonate Coarse Aggregate: Phase I, Progress Report, HR-337, 1992

The major objective of this research project is to utilize thermal analysis techniques in conjunction with x-ray analysis methods to identify and explain chemical reactions that promote aggregate related deterioration in Portland cement concrete. The first year of this project has been spent obtaining and analyzing limestone and dolomite samples that exhibit a wide range of field service performance. Most of the samples chosen for the study also had laboratory durability test information (ASTM C 666, method B) that was readily available. Preliminary test results indicate that a strong relationship exists between the average crystallite size of the limestone (calcite) specimens and their apparent decomposition temperatures as measured by thermogravimetric analysis. Also, premature weight loss in the thermogravimetric analysis tests appeared to be related to the apparent decomposition temperature of the various calcite test specimens.

Prediction of direct and indirect genetic gains and genotypic correlations in rubber tree progenies

The objective of this work was to estimate the genetic parameters, genotypic and phenotypic correlations, and direct and indirect genetic gains among and within rubber tree (Hevea brasiliensis) progenies. The experiment was set up at the Municipality of Jaú, SP, Brazil. A randomized complete block design was used, with 22 treatments (progenies), 6 replicates, and 10 plants per plot at a spacing of 3x3 m. Three‑year‑old progenies were assessed for girth, rubber yield, and bark thickness by direct and indirect gains and genotypic correlations. The number of latex vessel rings showed the best correlations, correlating positively and significantly with girth and bark thickness. Selection gains among progenies were greater than within progeny for all the variables analyzed. Total gains obtained were high, especially for girth increase and rubber yield, which were 93.38 and 105.95%, respectively. Young progeny selection can maximize the expected genetic gains, reducing the rubber tree selection cycle.

A comparison of Bayesian and frequentist approaches to incorporating external information for the prediction of prostate cancer risk.

We present the most comprehensive comparison to date of the predictive benefit of genetics in addition to currently used clinical variables, using genotype data for 33 single-nucleotide polymorphisms (SNPs) in 1,547 Caucasian men from the placebo arm of the REduction by DUtasteride of prostate Cancer Events (REDUCE®) trial. Moreover, we conducted a detailed comparison of three techniques for incorporating genetics into clinical risk prediction. The first method was a standard logistic regression model, which included separate terms for the clinical covariates and for each of the genetic markers. This approach ignores a substantial amount of external information concerning effect sizes for these Genome Wide Association Study (GWAS)-replicated SNPs. The second and third methods investigated two possible approaches to incorporating meta-analysed external SNP effect estimates - one via a weighted PCa 'risk' score based solely on the meta analysis estimates, and the other incorporating both the current and prior data via informative priors in a Bayesian logistic regression model. All methods demonstrated a slight improvement in predictive performance upon incorporation of genetics. The two methods that incorporated external information showed the greatest receiver-operating-characteristic AUCs increase from 0.61 to 0.64. The value of our methods comparison is likely to lie in observations of performance similarities, rather than difference, between three approaches of very different resource requirements. The two methods that included external information performed best, but only marginally despite substantial differences in complexity.

Prediction of hemodynamic severity of coarctation by magnetic resonance imaging.

A published formula containing minimal aortic cross-sectional area and the flow deceleration pattern in the descending aorta obtained by cardiovascular magnetic resonance predicts significant coarctation of the aorta (CoA). However, the existing formula is complicated to use in clinical practice and has not been externally validated. Consequently, its clinical utility has been limited. The aim of this study was to derive a simple and clinically practical algorithm to predict severe CoA from data obtained by cardiovascular magnetic resonance. Seventy-nine consecutive patients who underwent cardiovascular magnetic resonance and cardiac catheterization for the evaluation of native or recurrent CoA at Children's Hospital Boston (n = 30) and the University of California, San Francisco (n = 49), were retrospectively reviewed. The published formula derived from data obtained at Children's Hospital Boston was first validated from data obtained at the University of California, San Francisco. Next, pooled data from the 2 institutions were analyzed, and a refined model was created using logistic regression methods. Finally, recursive partitioning was used to develop a clinically practical prediction tree to predict transcatheter systolic pressure gradient ≥ 20 mm Hg. Severe CoA was present in 48 patients (61%). Indexed minimal aortic cross-sectional area and heart rate-corrected flow deceleration time in the descending aorta were independent predictors of CoA gradient ≥ 20 mm Hg (p <0.01 for both). A prediction tree combining these variables reached a sensitivity and specificity of 90% and 76%, respectively. In conclusion, the presented prediction tree on the basis of cutoff values is easy to use and may help guide the management of patients investigated for CoA.

Prediction of soil orders with high spatial resolution: response of different classifiers to sampling density

The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission errors, overall accuracy, and quantity and allocation disagreement. The decision tree was less sensitive to sampling density and had the highest accuracy and consistence. The SOM was the less sensitive and most consistent network. The MLP had a critical minimum and showed high inconsistency, whereas fuzzy ARTMap was more sensitive and less accurate. Results indicate that sampling densities used in conventional soil surveys can serve as a reference to predict soil orders in Serra Gaúcha.

Spatial prediction of monthly wind speeds in complex terrain with adaptive general regression neural networks

This paper presents the general regression neural networks (GRNN) as a nonlinear regression method for the interpolation of monthly wind speeds in complex Alpine orography. GRNN is trained using data coming from Swiss meteorological networks to learn the statistical relationship between topographic features and wind speed. The terrain convexity, slope and exposure are considered by extracting features from the digital elevation model at different spatial scales using specialised convolution filters. A database of gridded monthly wind speeds is then constructed by applying GRNN in prediction mode during the period 1968-2008. This study demonstrates that using topographic features as inputs in GRNN significantly reduces cross-validation errors with respect to low-dimensional models integrating only geographical coordinates and terrain height for the interpolation of wind speed. The spatial predictability of wind speed is found to be lower in summer than in winter due to more complex and weaker wind-topography relationships. The relevance of these relationships is studied using an adaptive version of the GRNN algorithm which allows to select the useful terrain features by eliminating the noisy ones. This research provides a framework for extending the low-dimensional interpolation models to high-dimensional spaces by integrating additional features accounting for the topographic conditions at multiple spatial scales. Copyright (c) 2012 Royal Meteorological Society.

Early prediction of response to sunitinib after imatinib failure by 18F-fluorodeoxyglucose positron emission tomography in patients with gastrointestinal stromal tumor.

PURPOSE: Positron emission tomography with (18)F-fluorodeoxyglucose (FDG-PET) was used to evaluate treatment response in patients with gastrointestinal stromal tumors (GIST) after administration of sunitinib, a multitargeted tyrosine kinase inhibitor, after imatinib failure. PATIENTS AND METHODS: Tumor metabolism was assessed with FDG-PET before and after the first 4 weeks of sunitinib therapy in 23 patients who received one to 12 cycles of sunitinib therapy (4 weeks of 50 mg/d, 2 weeks off). Treatment response was expressed as the percent change in maximal standardized uptake values (SUV). The primary end point of time to tumor progression was compared with early PET results on the basis of traditional Response Evaluation Criteria in Solid Tumors (RECIST) criteria. RESULTS: Progression-free survival (PFS) was correlated with early FDG-PET metabolic response (P < .0001). Using -25% and +25% thresholds for SUV variations from baseline, early FDG-PET response was stratified in metabolic partial response, metabolically stable disease, or metabolically progressive disease; median PFS rates were 29, 16, and 4 weeks, respectively. Similarly, when a single FDG-PET positive/negative was considered after 4 weeks of sunitinib, the median PFS was 29 weeks for SUVs less than 8 g/mL versus 4 weeks for SUVs of 8 g/mL or greater (P < .0001). None of the patients with metabolically progressive disease subsequently responded according to RECIST criteria. Multivariate analysis showed shorter PFS in patients who had higher residual SUVs (P < .0001), primary resistance to imatinib (P = .024), or nongastric GIST (P = .002), regardless of the mutational status of the KIT and PDGFRA genes. CONCLUSION: Week 4 FDG-PET is useful for early assessment of treatment response and for the prediction of clinical outcome. Thus, it offers opportunities to individualize and optimize patient therapy.

Comparison of plantar pressure distribution in adolescent runners at low vs. high running velocity

This study aimed to compare foot plantar pressure distribution while jogging and running in highly trained adolescent runners. Eleven participants performed two constant-velocity running trials either at jogging (11.2 ± 0.9 km/h) or running (17.8 ± 1.4 km/h) pace on a treadmill. Contact area (CA in cm(2)), maximum force (F(max) in N), peak pressure (PP in kPa), contact time (CT in ms), and relative load (force time integral in each individual region divided by the force time integral for the total plantar foot surface, in %) were measured in nine regions of the right foot using an in-shoe plantar pressure device. Under the whole foot, CA, F(max) and PP were lower in jogging than in running (-1.2% [p<0.05], -12.3% [p<0.001] and -15.1% [p<0.01] respectively) whereas CT was higher (+20.1%; p<0.001). Interestingly, we found an increase in relative load under the medial and central forefoot regions while jogging (+6.7% and +3.7%, respectively; [p<0.05]), while the relative load under the lesser toes (-8.4%; p<0.05) was reduced. In order to prevent overloading of the metatarsals in adolescent runners, excessive mileage at jogging pace should be avoided.

Prediction of soil shear strength in agricultural and natural environments of the Brazilian Cerrado

The objective of this work was to develop uni- and multivariate models to predict maximum soil shear strength (τmax) under different normal stresses (σn), water contents (U), and soil managements. The study was carried out in a Rhodic Haplustox under Cerrado (control area) and under no-tillage and conventional tillage systems. Undisturbed soil samples were taken in the 0.00-0.05 m layer and subjected to increasing U and σn, in shear strength tests. The uni- and multivariate models - respectively τmax=10(a+bU) and τmax=10(a+bU+cσn) - were significant in all three soil management systems evaluated and they satisfactorily explain the relationship between U, σn, and τmax. The soil under Cerrado has the highest shear strength (τ) estimated with the univariate model, regardless of the soil water content, whereas the soil under conventional tillage shows the highest values with the multivariate model, which were associated to the lowest water contents at the soil consistency limits in this management system.

The electricity distribution network in Saint-Petersburg area and benchmark between Saint-Petersburg and City of Stockholm related distribution companies' performance

The main objective of the Thesis is the description of the electricity distribution networks in Saint-Petersburg area and Stockholm as well. Main similarity and differences in the construction and technicalperformance are presented in the study. Present and future development and investment into the electricity distribution network of OJSC Lenenergo are viewed. The Thesis presents the overview of the power industry reform in Russia. The current state of the electricity distribution sector is described. The study views the participation of the foreign investor "Fortum Power and Heat Oy" inthe development and management of the OJSC Lenenergo. Benchmark comparison of the prices and tangible assets of the main electricity distribution companies in Saint-Petersburg and Stockholm areas is done.