956 resultados para Effects Based Operations


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BACKGROUND: The potential effects of ionizing radiation are of particular concern in children. The model-based iterative reconstruction VEO(TM) is a technique commercialized to improve image quality and reduce noise compared with the filtered back-projection (FBP) method. OBJECTIVE: To evaluate the potential of VEO(TM) on diagnostic image quality and dose reduction in pediatric chest CT examinations. MATERIALS AND METHODS: Twenty children (mean 11.4 years) with cystic fibrosis underwent either a standard CT or a moderately reduced-dose CT plus a minimum-dose CT performed at 100 kVp. Reduced-dose CT examinations consisted of two consecutive acquisitions: one moderately reduced-dose CT with increased noise index (NI = 70) and one minimum-dose CT at CTDIvol 0.14 mGy. Standard CTs were reconstructed using the FBP method while low-dose CTs were reconstructed using FBP and VEO. Two senior radiologists evaluated diagnostic image quality independently by scoring anatomical structures using a four-point scale (1 = excellent, 2 = clear, 3 = diminished, 4 = non-diagnostic). Standard deviation (SD) and signal-to-noise ratio (SNR) were also computed. RESULTS: At moderately reduced doses, VEO images had significantly lower SD (P < 0.001) and higher SNR (P < 0.05) in comparison to filtered back-projection images. Further improvements were obtained at minimum-dose CT. The best diagnostic image quality was obtained with VEO at minimum-dose CT for the small structures (subpleural vessels and lung fissures) (P < 0.001). The potential for dose reduction was dependent on the diagnostic task because of the modification of the image texture produced by this reconstruction. CONCLUSIONS: At minimum-dose CT, VEO enables important dose reduction depending on the clinical indication and makes visible certain small structures that were not perceptible with filtered back-projection.

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There is growing evidence that lymphocytes impact the development and/or function of other lymphocyte populations. Based on such observations we have tested whether the NK cell compartment was phenotypically and functionally altered in the absence of B and/or T cells. Here we show that T cell deficiency significantly accelerates BM NK cell production and the subsequent seeding of splenic and liver NK cell compartments. In contrast, B cell deficiency reduces splenic NK cell survival. In the absence of T and B cells, the size of the NK cell compartments is determined by the combination of these positive and negative effects. Even though NK cell homeostasis is significantly altered, NK cells from T and/or B cell-deficient mice show a normal capacity to kill a susceptible target cell line and to produce IFN. Nevertheless, we noted that the usage of MHC class I-specific Ly49 family receptors was significantly altered in the absence of T and/or B cells. In general, B cell deficiency expanded Ly49 receptor usage, while T cell deficiency exerted both positive and negative effects. These findings show that B and T cells significantly and differentially influence the homeostasis and the phenotype of NK cells.

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We describe the version of the GPT planner to be used in the planning competition. This version, called mGPT, solves mdps specified in the ppddllanguage by extracting and using different classes of lower bounds, along with various heuristic-search algorithms. The lower bounds are extracted from deterministic relaxations of the mdp where alternativeprobabilistic effects of an action are mapped into different, independent, deterministic actions. The heuristic-search algorithms, on the other hand, use these lower bounds for focusing the updates and delivering a consistent value function over all states reachable from the initial state with the greedy policy.

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The aim of this research was to investigate the effects of high pressure processing (HPP) on consumer acceptance for chilled ready meals manufactured using a low-value beef cut. Three hundred consumers evaluated chilled ready meals subjected to 4 pressure treatments and a non-treated control monadically on a 9-point scale for liking for beef tenderness and juiciness, overall flavour, overall liking, and purchase intent. Data were also collected on consumers' food consumption patterns, their attitudes towards food by means of the reduced food-related lifestyle (FRL) instrument, and socio-demographics. The results indicated that a pressure treatment of 200 MPa was acceptable to most consumers. K-means cluster analysis identified 4 consumer groups with similar preferences, and the optimal pressure treatments acceptable to specific consumer groups were identified for those firms that would wish to target attitudinally differentiated consumer segments

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Aim To evaluate the effects of using distinct alternative sets of climatic predictor variables on the performance, spatial predictions and future projections of species distribution models (SDMs) for rare plants in an arid environment. . Location Atacama and Peruvian Deserts, South America (18º30'S - 31º30'S, 0 - 3 000 m) Methods We modelled the present and future potential distributions of 13 species of Heliotropium sect. Cochranea, a plant group with a centre of diversity in the Atacama Desert. We developed and applied a sequential procedure, starting from climate monthly variables, to derive six alternative sets of climatic predictor variables. We used them to fit models with eight modelling techniques within an ensemble forecasting framework, and derived climate change projections for each of them. We evaluated the effects of using these alternative sets of predictor variables on performance, spatial predictions and projections of SDMs using Generalised Linear Mixed Models (GLMM). Results The use of distinct sets of climatic predictor variables did not have a significant effect on overall metrics of model performance, but had significant effects on present and future spatial predictions. Main conclusion Using different sets of climatic predictors can yield the same model fits but different spatial predictions of current and future species distributions. This represents a new form of uncertainty in model-based estimates of extinction risk that may need to be better acknowledged and quantified in future SDM studies.

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BACKGROUND & AIMS: Vitamin D is an important immune modulator and preliminary data indicated an association between vitamin D deficiency and sustained virologic response (SVR) rates in hepatitis C virus (HCV) genotype 1 patients. We, therefore, performed a comprehensive analysis on the impact of vitamin D serum levels and of genetic polymorphisms with functional relevance within the vitamin D cascade on chronic hepatitis C and its treatment. METHODS: Vitamin D serum levels, genetic polymorphisms within the vitamin D receptor and 1α-hydroxylase were determined in a cohort of 468 HCV genotype 1, 2, and 3 infected patients who were treated with interferon-alfa based regimens. RESULTS: Chronic hepatitis C was associated with a high incidence of severe vitamin D deficiency compared to controls (25(OH)D(3)<10 ng/ml in 25% versus 12%, p<0.00001). 25(OH)D(3) deficiency correlated with SVR in HCV genotype 2 and 3 patients (50% and 81% SVR for patients with and without severe vitamin D deficiency, respectively, p<0.0001). In addition, the CYP27B1-1260 promoter polymorphism rs10877012 had substantial impact on 1,25-dihydroxyvitamin D serum levels (72, 61, and 60 pmol/ml for rs10877012 AA, AC, and CC, respectively, p=0.04) and on SVR rates in HCV genotype 1, 2, and 3 infected patients (77% and 65% versus 42% for rs10877012 AA, AC, and CC, respectively, p=0.02). CONCLUSIONS: Chronic hepatitis C virus infection is associated with vitamin D deficiency. Reduced 25-hydroxyvitamin D levels and CYP27B1-1260 promoter polymorphism leading to reduced 1,25-dihydroxyvitamin D levels are associated with failure to achieve SVR in HCV genotype 1, 2, and 3 infected patients.

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Aim Species distribution models (SDMs) based on current species ranges underestimate the potential distribution when projected in time and/or space. A multi-temporal model calibration approach has been suggested as an alternative, and we evaluate this using 13,000 years of data. Location Europe. Methods We used fossil-based records of presence for Picea abies, Abies alba and Fagus sylvatica and six climatic variables for the period 13,000 to 1000yr bp. To measure the contribution of each 1000-year time step to the total niche of each species (the niche measured by pooling all the data), we employed a principal components analysis (PCA) calibrated with data over the entire range of possible climates. Then we projected both the total niche and the partial niches from single time frames into the PCA space, and tested if the partial niches were more similar to the total niche than random. Using an ensemble forecasting approach, we calibrated SDMs for each time frame and for the pooled database. We projected each model to current climate and evaluated the results against current pollen data. We also projected all models into the future. Results Niche similarity between the partial and the total-SDMs was almost always statistically significant and increased through time. SDMs calibrated from single time frames gave different results when projected to current climate, providing evidence of a change in the species realized niches through time. Moreover, they predicted limited climate suitability when compared with the total-SDMs. The same results were obtained when projected to future climates. Main conclusions The realized climatic niche of species differed for current and future climates when SDMs were calibrated considering different past climates. Building the niche as an ensemble through time represents a way forward to a better understanding of a species' range and its ecology in a changing climate.

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Radiation therapy undeniably enhances local control and thus improves overall survival in cancer patients. However, some long-term cancer survivors (less than 10%) develop severe late radio-induced toxicities altering their quality of life. Therefore, there is a need to identify patients who are sensitive to those toxicities and who could benefit from adapted care. In this review, we address all available techniques aiming to detect patients' hyper-radiosensitivity and present the scientific rationales these techniques are based on.

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We investigated the association between exposure to radio-frequency electromagnetic fields (RF-EMFs) from broadcast transmitters and childhood cancer. First, we conducted a time-to-event analysis including children under age 16 years living in Switzerland on December 5, 2000. Follow-up lasted until December 31, 2008. Second, all children living in Switzerland for some time between 1985 and 2008 were included in an incidence density cohort. RF-EMF exposure from broadcast transmitters was modeled. Based on 997 cancer cases, adjusted hazard ratios in the time-to-event analysis for the highest exposure category (>0.2 V/m) as compared with the reference category (<0.05 V/m) were 1.03 (95% confidence interval (CI): 0.74, 1.43) for all cancers, 0.55 (95% CI: 0.26, 1.19) for childhood leukemia, and 1.68 (95% CI: 0.98, 2.91) for childhood central nervous system (CNS) tumors. Results of the incidence density analysis, based on 4,246 cancer cases, were similar for all types of cancer and leukemia but did not indicate a CNS tumor risk (incidence rate ratio = 1.03, 95% CI: 0.73, 1.46). This large census-based cohort study did not suggest an association between predicted RF-EMF exposure from broadcasting and childhood leukemia. Results for CNS tumors were less consistent, but the most comprehensive analysis did not suggest an association.

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We propose a novel multifactor dimensionality reduction method for epistasis detection in small or extended pedigrees, FAM-MDR. It combines features of the Genome-wide Rapid Association using Mixed Model And Regression approach (GRAMMAR) with Model-Based MDR (MB-MDR). We focus on continuous traits, although the method is general and can be used for outcomes of any type, including binary and censored traits. When comparing FAM-MDR with Pedigree-based Generalized MDR (PGMDR), which is a generalization of Multifactor Dimensionality Reduction (MDR) to continuous traits and related individuals, FAM-MDR was found to outperform PGMDR in terms of power, in most of the considered simulated scenarios. Additional simulations revealed that PGMDR does not appropriately deal with multiple testing and consequently gives rise to overly optimistic results. FAM-MDR adequately deals with multiple testing in epistasis screens and is in contrast rather conservative, by construction. Furthermore, simulations show that correcting for lower order (main) effects is of utmost importance when claiming epistasis. As Type 2 Diabetes Mellitus (T2DM) is a complex phenotype likely influenced by gene-gene interactions, we applied FAM-MDR to examine data on glucose area-under-the-curve (GAUC), an endophenotype of T2DM for which multiple independent genetic associations have been observed, in the Amish Family Diabetes Study (AFDS). This application reveals that FAM-MDR makes more efficient use of the available data than PGMDR and can deal with multi-generational pedigrees more easily. In conclusion, we have validated FAM-MDR and compared it to PGMDR, the current state-of-the-art MDR method for family data, using both simulations and a practical dataset. FAM-MDR is found to outperform PGMDR in that it handles the multiple testing issue more correctly, has increased power, and efficiently uses all available information.

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This project develops a smartphone-based prototype system that supplements the 511 system to improve its dynamic traffic routing service to state highway users under non-recurrent congestion. This system will save considerable time to provide crucial traffic information and en-route assistance to travelers for them to avoid being trapped in traffic congestion due to accidents, work zones, hazards, or special events. It also creates a feedback loop between travelers and responsible agencies that enable the state to effectively collect, fuse, and analyze crowd-sourced data for next-gen transportation planning and management. This project can result in substantial economic savings (e.g. less traffic congestion, reduced fuel wastage and emissions) and safety benefits for the freight industry and society due to better dissemination of real-time traffic information by highway users. Such benefits will increase significantly in future with the expected increase in freight traffic on the network. The proposed system also has the flexibility to be integrated with various transportation management modules to assist state agencies to improve transportation services and daily operations.

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The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

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Pro-inflammatory cytokines and high-sensitive C-reactive protein (hs-CRP) are associated with increased risk for cardiovascular disease. Low-dose aspirin for CV prevention is reported to have anti-inflammatory effects. The aim of this study was to determine the association between pro-inflammatory cytokines and hs-CRP levels and low-dose aspirin use for cardiovascular prevention in a population-based cohort (CoLaus Study). We assessed blood samples in 6085 participants (3201 women) aged 35-75years. Medications' use and indications were recorded. Among aspirin users (n=1'034; 17%), overall low-dose users (351; 5.8%) and low-dose for cardiovascular prevention users (324; 5.3%) were selected for analysis. Pro-inflammatory cytokines (IL-1β, IL-6 and TNF-α were assessed by a multiplex particle-based flow cytometric assay and hs-CRP by an immunometric assay. Cytokines and hs-CRP were presented in quartiles. Multivariate analysis adjusting for sex, age, smoking status, body mass index, diabetes mellitus and immunomodulatory drugs showed no association between cytokines and hs-CRP levels and low-dose aspirin use for cardiovascular prevention, either comparing the topmost vs. the three other quartiles (OR 95% CI, 0.84 (0.59-1.18), 1.03 (0.78-1.32), 1.10 (0.83-1.46), 1.00 (0.67-1.69) for IL-1β, IL-6, TNF-α and hs-CRP, respectively), or comparing the topmost quartile vs. the first one (OR 95% CI, 0.87 (0.60-1.26), 1.19 (0.79-1.79), 1.26 (0.86-1.84), 1.06 (0.67-1.69)). Low-dose aspirin use for cardiovascular prevention does not impact plasma pro-inflammatory cytokine and hs-CRP levels in a population-based cohort.

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Alzheimer’s disease (AD) is the most prevalent form of progressive degenerative dementia and it has a high socio-economic impact in Western countries, therefore is one of the most active research areas today. Its diagnosis is sometimes made by excluding other dementias, and definitive confirmation must be done trough a post-mortem study of the brain tissue of the patient. The purpose of this paper is to contribute to im-provement of early diagnosis of AD and its degree of severity, from an automatic analysis performed by non-invasive intelligent methods. The methods selected in this case are Automatic Spontaneous Speech Analysis (ASSA) and Emotional Temperature (ET), that have the great advantage of being non invasive, low cost and without any side effects.

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Behavioral and physiological responses to unpredictable changes in environmental conditions are, in part, mediated by glucocorticoids (corticosterone in birds). In polymorphic species, individuals of the same sex and age display different heritable melanin-based color morphs, associated with physiological and reproductive parameters and possibly alternative strategies to cope with variation in environmental conditions. We examined whether the role of corticosterone in resolving the trade-off between self-maintenance and reproductive activities covaries with the size of melanin-based spots displayed on the ventral body side of male barn owls. Administration of corticosterone to simulate physiological stress in males revealed pronounced changes in their food-provisioning rates to nestlings compared to control males. Corticosterone-treated males with small eumelanic spots reduced nestling provisioning rates as compared to controls, and also to a greater degree than did corticosterone-treated males with large spots. Large-spotted males generally exhibited lower parental provisioning and appear insensitive to exogenous corticosterone suggesting that the size of the black spots on the breast feathers predicts the ability to cope with stressful situations. The reduced provisioning rate of corticosterone-treated males caused a temporary reduction in nestling growth rates but, did not affect fledgling success. This suggests that moderately elevated corticosterone levels are not inhibitory to current reproduction but rather trigger behavioral responses to maximize lifetime reproductive success.