985 resultados para Crowd density estimation
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The objective of this work was to evaluate the effects of high density planting on 'Tommy Atkins' mango trees cultivated in subhumid warm tropical climate in northeastern Brazil. Treatments consisted of five spacial arrangements of plants (8x5 m, 7x4 m, 6x3 m, 5x2 m and 4x2 m), which resulted in the following plant densities: 250 (control), 357, 555, 1,000 and 1,250 plants per hectare. Plant vegetative and reproductive variables, besides fruit quality parameters, were evaluated at seven and eight years after transplantation to the field. In general, high density planting caused reduction in vegetative and reproductive variables of individual mango trees, but had little influence on fruit quality. Above 555 plants per hectare, a significant decrease was observed in mango tree growth. Furthermore, there were decreases in the percentage of flowering, fruit yield per plant and per area. However, planting density up to 357 plants per hectare, in spite of decreasing plant growth and fruit yield per tree, increases fruit yield per area in 30% in comparison to the control.
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Dose kernel convolution (DK) methods have been proposed to speed up absorbed dose calculations in molecular radionuclide therapy. Our aim was to evaluate the impact of tissue density heterogeneities (TDH) on dosimetry when using a DK method and to propose a simple density-correction method. METHODS: This study has been conducted on 3 clinical cases: case 1, non-Hodgkin lymphoma treated with (131)I-tositumomab; case 2, a neuroendocrine tumor treatment simulated with (177)Lu-peptides; and case 3, hepatocellular carcinoma treated with (90)Y-microspheres. Absorbed dose calculations were performed using a direct Monte Carlo approach accounting for TDH (3D-RD), and a DK approach (VoxelDose, or VD). For each individual voxel, the VD absorbed dose, D(VD), calculated assuming uniform density, was corrected for density, giving D(VDd). The average 3D-RD absorbed dose values, D(3DRD), were compared with D(VD) and D(VDd), using the relative difference Δ(VD/3DRD). At the voxel level, density-binned Δ(VD/3DRD) and Δ(VDd/3DRD) were plotted against ρ and fitted with a linear regression. RESULTS: The D(VD) calculations showed a good agreement with D(3DRD). Δ(VD/3DRD) was less than 3.5%, except for the tumor of case 1 (5.9%) and the renal cortex of case 2 (5.6%). At the voxel level, the Δ(VD/3DRD) range was 0%-14% for cases 1 and 2, and -3% to 7% for case 3. All 3 cases showed a linear relationship between voxel bin-averaged Δ(VD/3DRD) and density, ρ: case 1 (Δ = -0.56ρ + 0.62, R(2) = 0.93), case 2 (Δ = -0.91ρ + 0.96, R(2) = 0.99), and case 3 (Δ = -0.69ρ + 0.72, R(2) = 0.91). The density correction improved the agreement of the DK method with the Monte Carlo approach (Δ(VDd/3DRD) < 1.1%), but with a lesser extent for the tumor of case 1 (3.1%). At the voxel level, the Δ(VDd/3DRD) range decreased for the 3 clinical cases (case 1, -1% to 4%; case 2, -0.5% to 1.5%, and -1.5% to 2%). No more linear regression existed for cases 2 and 3, contrary to case 1 (Δ = 0.41ρ - 0.38, R(2) = 0.88) although the slope in case 1 was less pronounced. CONCLUSION: This study shows a small influence of TDH in the abdominal region for 3 representative clinical cases. A simple density-correction method was proposed and improved the comparison in the absorbed dose calculations when using our voxel S value implementation.
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The objective of this work was to develop a procedure to estimate soybean crop areas in Rio Grande do Sul state, Brazil. Estimations were made based on the temporal profiles of the enhanced vegetation index (Evi) calculated from moderate resolution imaging spectroradiometer (Modis) images. The methodology developed for soybean classification was named Modis crop detection algorithm (MCDA). The MCDA provides soybean area estimates in December (first forecast), using images from the sowing period, and March (second forecast), using images from the sowing and maximum crop development periods. The results obtained by the MCDA were compared with the official estimates on soybean area of the Instituto Brasileiro de Geografia e Estatística. The coefficients of determination ranged from 0.91 to 0.95, indicating good agreement between the estimates. For the 2000/2001 crop year, the MCDA soybean crop map was evaluated using a soybean crop map derived from Landsat images, and the overall map accuracy was approximately 82%, with similar commission and omission errors. The MCDA was able to estimate soybean crop areas in Rio Grande do Sul State and to generate an annual thematic map with the geographic position of the soybean fields. The soybean crop area estimates by the MCDA are in good agreement with the official agricultural statistics.
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PURPOSE: To use measurement by cycling power meters (Pmes) to evaluate the accuracy of commonly used models for estimating uphill cycling power (Pest). Experiments were designed to explore the influence of wind speed and steepness of climb on accuracy of Pest. The authors hypothesized that the random error in Pest would be largely influenced by the windy conditions, the bias would be diminished in steeper climbs, and windy conditions would induce larger bias in Pest. METHODS: Sixteen well-trained cyclists performed 15 uphill-cycling trials (range: length 1.3-6.3 km, slope 4.4-10.7%) in a random order. Trials included different riding position in a group (lead or follow) and different wind speeds. Pmes was quantified using a power meter, and Pest was calculated with a methodology used by journalists reporting on the Tour de France. RESULTS: Overall, the difference between Pmes and Pest was -0.95% (95%CI: -10.4%, +8.5%) for all trials and 0.24% (-6.1%, +6.6%) in conditions without wind (<2 m/s). The relationship between percent slope and the error between Pest and Pmes were considered trivial. CONCLUSIONS: Aerodynamic drag (affected by wind velocity and orientation, frontal area, drafting, and speed) is the most confounding factor. The mean estimated values are close to the power-output values measured by power meters, but the random error is between ±6% and ±10%. Moreover, at the power outputs (>400 W) produced by professional riders, this error is likely to be higher. This observation calls into question the validity of releasing individual values without reporting the range of random errors.
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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.
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The effectiveness of lipid-lowering medication critically depends on the patients' compliance and the efficacy of the prescribed drug. The primary objective of this multicentre study was to compare the efficacy of rosuvastatin with or without access to compliance initiatives, in bringing patients to the Joint European Task Force's (1998) recommended low-density lipoprotein cholesterol (LDL-C) level goal (LDL-C, <3.0 mmol/L) at week 24. Secondary objectives were comparison of the number and percentage of patients achieving European goals (1998, 2003) for LDL-C and other lipid parameters. Patients with primary hypercholesterolaemia and a 10-year coronary heart disease risk of >20% received open label rosuvastatin treatment for 24 weeks with or without access to compliance enhancement tools. The initial daily dosage of 10 mg could be doubled at week 12. Compliance tools included: a) a starter pack for subjects containing a videotape, an educational leaflet, a passport/goal diary and details of the helpline and/or website; b) regular personalised letters to provide message reinforcement; c) a toll-free helpline and a website. The majority of patients (67%) achieved the 1998 European goal for LDL-C at week 24. 31% required an increase in dosage of rosuvastatin to 20 mg at week 12. Compliance enhancement tools did not increase the number of patients achieving either the 1998 or the 2003 European target for plasma lipids. Rosuvastatin was well tolerated during this study. The safety profile was comparable with other drugs of the same class. 63 patients in the 10 mg group and 58 in the 10 mg Plus group discontinued treatment. The main reasons for discontinuation were adverse events (39 patients in the 10 mg group; 35 patients in the 10 mg Plus group) and loss to follow-up (13 patients in the 10 mg group; 9 patients in the 10 mg Plus group). The two most frequently reported adverse events were myalgia (34 patients, 3% respectively) and back pain (23 patients, 2% respectively). The overall rate of temporary or permanent study discontinuation due to adverse events was 9% (n = 101) in patients receiving 10 mg rosuvastatin and 3% (n = 9) in patients titrated up to 20 mg rosuvastatin. Rosuvastatin was effective in lowering LDL-C values in patients with hypercholesterolaemia to the 1998 European target at week 24. However, compliance enhancement tools did not increase the number of patients achieving any European targets for plasma lipids.
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AIMS/HYPOTHESIS: We explored the potential adverse effects of pro-atherogenic oxidised LDL-cholesterol particles on beta cell function. MATERIALS AND METHODS: Isolated human and rat islets and different insulin-secreting cell lines were incubated with human oxidised LDL with or without HDL particles. The insulin level was monitored by ELISA, real-time PCR and a rat insulin promoter construct linked to luciferase gene reporter. Cell apoptosis was determined by scoring cells displaying pycnotic nuclei. RESULTS: Prolonged incubation with human oxidised LDL particles led to a reduction in preproinsulin expression levels, whereas the insulin level was preserved in the presence of native LDL-cholesterol. The loss of insulin production occurred at the transcriptional levels and was associated with an increase in activator protein-1 transcriptional activity. The rise in activator protein-1 activity resulted from activation of c-Jun N-terminal kinases (JNK, now known as mitogen-activated protein kinase 8 [MAPK8]) due to a subsequent decrease in islet-brain 1 (IB1; now known as MAPK8 interacting protein 1) levels. Consistent with the pro-apoptotic role of the JNK pathway, oxidised LDL also induced a twofold increase in the rate of beta cell apoptosis. Treatment of the cells with JNK inhibitor peptides or HDL countered the effects mediated by oxidised LDL. CONCLUSIONS/INTERPRETATION: These data provide strong evidence that oxidised LDL particles exert deleterious effects in the progression of beta cell failure in diabetes and that these effects can be countered by HDL particles.