832 resultados para Poisson generalized linear mixed models
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EXTRACT (SEE PDF FOR FULL ABSTRACT): High-resolution proxy records of climate, such as varves, ice cores, and tree-rings, provide the opportunity for reconstructing climate on a year-by-year basis. In order to do so it is necessary to approximate the complex nonlinear response function of the natural recording system using linear statistical models. Three problems with this approach were discussed, and possible solutions were suggested. Examples were given from a reconstruction of Santa Barbara precipitation based on tree-ring records from Santa Barbara County.
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Linear regression models are constructed to predict seasonal runoff by fitting streamflow to temperature, precipitation, and snow water content across a range of elevations. The models are quite successful in capturing the differences in discharge between different elevation watersheds and their interannual variations. This exercise thus provides insight into seasonal changes in streamflow at different elevation watersheds that might occur under a changed climate.
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Jumbo squid (Dosidicus gigas) and purpleback squid (Sthenoteuthis oualaniensis) (Teuthida: Ommastrephidae) are thought to spawn in the eastern tropical Pacific. We used 10 years of plankton tow and oceanographic data collected in this region to examine the reproductive habits of these 2 ecologically important squid. Paralarvae of jumbo squid and purpleback squid were found in 781 of 1438 plankton samples from surface and oblique tows conducted by the Southwest Fisheries Science Center (NOAA) in the eastern tropical Pacific over the 8-year period of 1998–2006. Paralarvae were far more abundant in surface tows (maximum: 1588 individuals) than in oblique tows (maximum: 64 individuals). A generalized linear model analysis revealed sea-surface temperature as the strongest environmental predictor of paralarval presence in both surface and oblique tows; the likelihood of paralarval presence increases with increasing temperature. We used molecular techniques to identify paralarvae from 37 oblique tows to species level and found that the purpleback squid was more abundant than the jumbo squid (81 versus 16 individuals).
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We show that the sensor self-localization problem can be cast as a static parameter estimation problem for Hidden Markov Models and we implement fully decentralized versions of the Recursive Maximum Likelihood and on-line Expectation-Maximization algorithms to localize the sensor network simultaneously with target tracking. For linear Gaussian models, our algorithms can be implemented exactly using a distributed version of the Kalman filter and a novel message passing algorithm. The latter allows each node to compute the local derivatives of the likelihood or the sufficient statistics needed for Expectation-Maximization. In the non-linear case, a solution based on local linearization in the spirit of the Extended Kalman Filter is proposed. In numerical examples we demonstrate that the developed algorithms are able to learn the localization parameters. © 2012 IEEE.
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Hybrid methods based on the Reynolds Averaged Navier Stokes (RANS) equations and the Large Eddy Simulation (LES) formulation are investigated to try and improve the accuracy of heat transfer and surface temperature predictions for electronics systems and components. Two relatively low Reynolds number flows are studied using hybrid RANS-LES, RANS-Implicit-LES (RANS-ILES) and non-linear LES models. Predictions using these methods are in good agreement with each other, even using different grid resolutions. © 2008 IEEE.
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The ovaries of Kun-Ming strain mice (3 weeks) were irradiated with different doses of C-12(6+) ion or Co-60 gamma-ray. Chromosomal aberrations were analyzed in metaphase II oocytes at 7 weeks after irradiation. The relative biological effectiveness (RBE) of C C-12(6+) ion was calculated with respect to Co-60 gamma-ray for the induction of chromosornal aberrations. The C-12(6+) ion and Co-60 gamma-ray dose-response relationships for chromosomal aberrations were plotted by linear quadratic models. The data showed that there was a dose-related increase in frequency of chromosomal aberrations in all the treated groups compared to controls. The RBE values for C-12(6+) ions relative to (CO)-C-60 gamma-rays were 2.49, 2.29, 1.57, 1.42 or 1.32 for the doses of 0.5, 1.0, 2.07 4.0 or 6.0 Gy, respectively. Moreover, a different distribution of the various types of aberrations has been found for C-12(6+) ion and Co-60 gamma-ray irradiations. The dose-response relationships for C-12(6+) ion and (CO)-C-60 gamma-ray exhibited positive correlations. The results from the present study may be helpful for assessing genetic damage following exposure of immature oocytes to ionizing radiation.
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The modeling formula based on seismic wavelet can well simulate zero - phase wavelet and hybrid-phase wavelet, and approximate maximal - phase and minimal - phase wavelet in a certain sense. The modeling wavelet can be used as wavelet function after suitable modification item added to meet some conditions. On the basis of the modified Morlet wavelet, the derivative wavelet function has been derived. As a basic wavelet, it can be sued for high resolution frequency - division processing and instantaneous feature extraction, in acoordance with the signal expanding characters in time and scale domains by each wavelet structured. Finally, an application example proves the effectiveness and reasonability of the method. Based on the analysis of SVD (Singular Value Decomposition) filter, by taking wavelet as basic wavelet and combining SVD filter and wavelet transform, a new de - noising method, which is Based on multi - dimension and multi-space de - noising method, is proposed. The implementation of this method is discussed the detail. Theoretical analysis and modeling show that the method has strong capacity of de - noising and keeping attributes of effective wave. It is a good tool for de - noising when the S/N ratio is poor. To give prominence to high frequency information of reflection event of important layer and to take account of other frequency information under processing seismic data, it is difficult for deconvolution filter to realize this goal. A filter from Fourier Transform has some problems for realizing the goal. In this paper, a new method is put forward, that is a method of processing seismic data in frequency division from wavelet transform and reconstruction. In ordinary seismic processing methods for resolution improvement, deconvolution operator has poor part characteristics, thus influencing the operator frequency. In wavelet transform, wavelet function has very good part characteristics. Frequency - division data processing in wavelet transform also brings quite good high resolution data, but it needs more time than deconvolution method does. On the basis of frequency - division processing method in wavelet domain, a new technique is put forward, which involves 1) designing filter operators equivalent to deconvolution operator in time and frequency domains in wavelet transform, 2) obtaining derivative wavelet function that is suitable to high - resolution seismic data processing, and 3) processing high resolution seismic data by deconvolution method in time domain. In the method of producing some instantaneous characteristic signals by using Hilbert transform, Hilbert transform is very sensitive to high - frequency random noise. As a result, even though there exist weak high - frequency noises in seismic signals, the obtained instantaneous characteristics of seismic signals may be still submerged by the noises. One method for having instantaneous characteristics of seismic signals in wavelet domain is put forward, which obtains directly the instantaneous characteristics of seismic signals by taking the characteristics of both the real part (real signals, namely seismic signals) and the imaginary part (the Hilbert transfom of real signals) of wavelet transform. The method has the functions of frequency division and noise removal. What is more, the weak wave whose frequency is lower than that of high - frequency random noise is retained in the obtained instantaneous characteristics of seismic signals, and the weak wave may be seen in instantaneous characteristic sections (such as instantaneous frequency, instantaneous phase and instantaneous amplitude). Impedance inversion is one of tools in the description of oil reservoir. one of methods in impedance inversion is Generalized Linear Inversion. This method has higher precision of inversion. But, this method is sensitive to noise of seismic data, so that error results are got. The description of oil reservoir in researching important geological layer, in order to give prominence to geological characteristics of the important layer, not only high frequency impedance to research thin sand layer, but other frequency impedance are needed. It is difficult for some impedance inversion method to realize the goal. Wavelet transform is very good in denoising and processing in frequency division. Therefore, in the paper, a method of impedance inversion is put forward based on wavelet transform, that is impedance inversion in frequency division from wavelet transform and reconstruction. in this paper, based on wavelet transform, methods of time - frequency analysis is given. Fanally, methods above are in application on real oil field - Sansan oil field.
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This paper analyzes landsliding process by nonlinear theories, especially the influence mechanism of external factors (such as rainfall and groundwater) on slope evolution. The author investigates landslide as a consequence of the catastrophic slide of initially stationary or creeping slope triggered by a small perturbation. A fully catastrophe analysis is done for all possible scenarios when a continuous change is imposed to the control parameters. As the slip surface continues and erosion due to rainfall occurs, control parameters of the slip surface may evolve such that a previously stable slope may become unstable (e.g. catastrophe occurs), when a small perturbation is imposed. Thus the present analysis offers a plausible explanation to why slope failure occurs at a particular rainfall, which is not the largest in the history of the slope. It is found, by analysis on the nonlinear dynamical model of the evolution process of slope built, that the relationship between the action of external environment factors and the response of the slope system is complicatedly nonlinear. When the nonlinear action of slope itself is equivalent to the acting ability of external environment, the chaotic phenomenon appears in the evolution process of slope, and its route leading to chaos is realized with bifurcation of period-doublings. On the basis of displacement time series of the slope, a nonlinear dynamic model is set up by improved Backus generalized linear inversion theory in this paper. Due to the equivalence between autonomous gradient system and catastrophe model, a standard cusp catastrophe model can be obtained through variable substitution. The method is applied to displacement data of Huangci landslide and Wolongsi landslide, to show how slopes evolve before landsliding. There is convincing statistical evidence to believe that the nonlinear dynamic model can make satisfied prediction results. Most important of all, we find that there is a sudden fall of D, which indicates the occurrence of catastrophe (when D=0).
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Saprolite is the residual soil resulted from completely weathered or highly weathered granite and with corestones of parent rock. It is widely distributed in Hong Kong. Slope instability usually happens in this layer of residual soil and thus it is very important to study the engineering geological properties of Saprolite. Due to the relic granitic texture, the deformation and strength characteristics of Saprolite are very different from normal residual soils. In order to investigate the effects of the special microstructure on soil deformation and strength, a series of physical, chemical and mechanical tests were conducted on Saprolite at Kowloon, Hong Kong. The tests include chemical analysis, particle size analysis, mineral composition analysis, mercury injection, consolidation test, direct shear test, triaxial shear test, optical analysis, SEM & TEM analysis, and triaxial shear tests under real-time CT monitoring.Based on the testing results, intensity and degree of weathering were classified, factors affecting and controlling the deformation and strength of Saprolite were identified, and the interaction between those factors were analyzed.The major parameters describing soil microstructure were introduced mainly based on optical thin section analysis results. These parameters are of importance and physical meaning to describe particle shape, particle size distribution (PSD), and for numerical modeling of soil microstructure. A few parameters to depict particle geometry were proposed or improved. These parameters can be used to regenerate the particle shape and its distribution. Fractal dimension of particle shape was proposed to describe irregularity of particle shapes and capacity of space filling quantitatively. And the effect of fractal dimension of particle shape on soil strength was analyzed. At the same time, structural coefficient - a combined parameter which can quantify the overall microstructure of rock or soil was introduced to study Saprolite and the results are very positive. The study emphasized on the fractal characteristics of PSD and pore structure by applying fractal theory and method. With the results from thin section analysis and mercury injection, it was shown that at least two fractal dimensions Dfl(DB) and Df2 (Dw), exist for both PSD and pore structure. The reasons and physical meanings behind multi-fractal dimensions were analyzed. The fractal dimensions were used to calculate the formation depth and weathering rate of granite at Kowloon. As practical applications, correlations and mathematical models for fractal dimensions and engineering properties of soil were established. The correlation between fractal dimensions and mechanical properties of soil shows that the internal friction angle is mainly governed by Dfl 9 corresponding to coarse grain components, while the cohesion depends on Df2 , corresponding to fine grain components. The correlations between the fractal dimension, friction angle and cohesion are positive linear.Fractal models of PSD and pore size distribution were derived theoretically. Fragmentation mechanism of grains was also analyzed from the viewpoint of fractal. A simple function was derived to define the theoretical relationship between the water characteristic curve (WCC) and fractal dimension, based on a number of classical WCC models. This relationship provides a new analytical tool and research method for hydraulic properties in porous media and solute transportation. It also endues fractal dimensions with new physical meanings and facilitates applications of fractal dimensions in water retention characteristics, ground water movement, and environmental engineering.Based on the conclusions from the fractal characteristics of Saprolite, size effect on strength was expressed by fractal dimension. This function is in complete agreement with classical Weibull model and a simple function was derived to represent the relationship between them.In this thesis, the phenomenon of multi-fractal dimensions was theoretically analyzed and verified with WCC and saprolite PSD results, it was then concluded that multi-fractal can describe the characteristics of one object more accurately, compared to single fractal dimension. The multi-fractal of saprolite reflects its structural heterogeneity and changeable stress environment during the evolution history.
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Sk?t, L., Humphreys, J., Humphreys, M. O., Thorogood, D., Gallagher, J. A., Sanderson, R., Armstead, I. P., Thomas, I. D. (2007). Association of candidate genes with flowering time and water-soluble carbohydrate content in Lolium perenne (L.). Genetics, 177 (1), 535-547. Sponsorship: BBSRC RAE2008
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As a prominent form of land use across much of upland Europe, extensive livestock grazing may hold the key to the sustainable management of these landscapes. Recent agricultural policy reform, however, has resulted in a decline in upland sheep numbers, prompting concern for the biodiversity value of these areas. This study quantifies the effects of varying levels of grazing management on plant, ground beetle and breeding bird diversity and assemblage in the uplands and lowlands of hill sheep farms in County Kerry, Ireland. Farms represent a continuum of light to heavy grazing, measured using a series of field indicators across several habitats, such as the internationally important blanket bog, home to the ground beetle, Carabus clatratus. Linear mixed effects modelling and non-metric multidimensional scaling are employed to disentangle the most influential management and environmental factors. Grazing state may be determined by the presence of Molinia caerulea or Nardus stricta, and variables such as % traditional ewes, % vegetation litter and % scrub prove valuable indicators of diversity. Measures of ecosystem functioning, e.g. plant biomass (nutrient cycling) and % vegetation cover (erosion rates) are influenced by plant diversity, which is influenced by grazing management. Levels of the ecosystem service, soil organic carbon, vary with ground beetle abundance and diversity, potentially influencing carbon sequestration and thereby climate change. The majority of species from all three taxa are found in the lowlands, with the exception of birds such as meadow pipit and skylark. The scale of measurement should be determined by the size and mobility of the species in question. The challenge is to manage these high nature value landscapes using agri-environment schemes which enhance biodiversity by maintaining structural heterogeneity across a range of scales, altitudes and habitats whilst integrating the decisions of people living and working in these marginal areas.
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BACKGROUND: Stroke is one of the most disabling and costly impairments of adulthood in the United States. Stroke patients clearly benefit from intensive inpatient care, but due to the high cost, there is considerable interest in implementing interventions to reduce hospital lengths of stay. Early discharge rehabilitation programs require coordinated, well-organized home-based rehabilitation, yet lack of sufficient information about the home setting impedes successful rehabilitation. This trial examines a multifaceted telerehabilitation (TR) intervention that uses telehealth technology to simultaneously evaluate the home environment, assess the patient's mobility skills, initiate rehabilitative treatment, prescribe exercises tailored for stroke patients and provide periodic goal oriented reassessment, feedback and encouragement. METHODS: We describe an ongoing Phase II, 2-arm, 3-site randomized controlled trial (RCT) that determines primarily the effect of TR on physical function and secondarily the effect on disability, falls-related self-efficacy, and patient satisfaction. Fifty participants with a diagnosis of ischemic or hemorrhagic stroke will be randomly assigned to one of two groups: (a) TR; or (b) Usual Care. The TR intervention uses a combination of three videotaped visits and five telephone calls, an in-home messaging device, and additional telephonic contact as needed over a 3-month study period, to provide a progressive rehabilitative intervention with a treatment goal of safe functional mobility of the individual within an accessible home environment. Dependent variables will be measured at baseline, 3-, and 6-months and analyzed with a linear mixed-effects model across all time points. DISCUSSION: For patients recovering from stroke, the use of TR to provide home assessments and follow-up training in prescribed equipment has the potential to effectively supplement existing home health services, assist transition to home and increase efficiency. This may be particularly relevant when patients live in remote locations, as is the case for many veterans. TRIAL REGISTRATION: Clinical Trials.gov Identifier: NCT00384748.
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BACKGROUND: Dropouts and missing data are nearly-ubiquitous in obesity randomized controlled trails, threatening validity and generalizability of conclusions. Herein, we meta-analytically evaluate the extent of missing data, the frequency with which various analytic methods are employed to accommodate dropouts, and the performance of multiple statistical methods. METHODOLOGY/PRINCIPAL FINDINGS: We searched PubMed and Cochrane databases (2000-2006) for articles published in English and manually searched bibliographic references. Articles of pharmaceutical randomized controlled trials with weight loss or weight gain prevention as major endpoints were included. Two authors independently reviewed each publication for inclusion. 121 articles met the inclusion criteria. Two authors independently extracted treatment, sample size, drop-out rates, study duration, and statistical method used to handle missing data from all articles and resolved disagreements by consensus. In the meta-analysis, drop-out rates were substantial with the survival (non-dropout) rates being approximated by an exponential decay curve (e(-lambdat)) where lambda was estimated to be .0088 (95% bootstrap confidence interval: .0076 to .0100) and t represents time in weeks. The estimated drop-out rate at 1 year was 37%. Most studies used last observation carried forward as the primary analytic method to handle missing data. We also obtained 12 raw obesity randomized controlled trial datasets for empirical analyses. Analyses of raw randomized controlled trial data suggested that both mixed models and multiple imputation performed well, but that multiple imputation may be more robust when missing data are extensive. CONCLUSION/SIGNIFICANCE: Our analysis offers an equation for predictions of dropout rates useful for future study planning. Our raw data analyses suggests that multiple imputation is better than other methods for handling missing data in obesity randomized controlled trials, followed closely by mixed models. We suggest these methods supplant last observation carried forward as the primary method of analysis.
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This research tested if a 12-session coping improvement group intervention (n = 104) reduced depressive symptoms in HIV-infected older adults compared to an interpersonal support group intervention (n = 105) and an individual therapy upon request (ITUR) control condition (n = 86). Participants were 295 HIV-infected men and women 50-plus years of age living in New York City, Cincinnati, OH, and Columbus, OH. Using A-CASI assessment methodology, participants provided data on their depressive symptoms using the Geriatric Depression Screening Scale (GDS) at pre-intervention, post-intervention, and 4- and 8-month follow-up. Whether conducted with all participants (N = 295) or only a subset of participants diagnosed with mild, moderate, or severe depressive symptoms (N = 171), mixed models analyses of repeated measures found that both coping improvement and interpersonal support group intervention participants reported fewer depressive symptoms than ITUR controls at post-intervention, 4-month follow-up, and 8-month follow-up. The effect sizes of the differences between the two active interventions and the control group were greater when outcome analyses were limited to those participants with mild, moderate, or severe depressive symptoms. At no assessment period did coping improvement and interpersonal support group intervention participants differ in depressive symptoms.
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X-ray crystallography is the predominant method for obtaining atomic-scale information about biological macromolecules. Despite the success of the technique, obtaining well diffracting crystals still critically limits going from protein to structure. In practice, the crystallization process proceeds through knowledge-informed empiricism. Better physico-chemical understanding remains elusive because of the large number of variables involved, hence little guidance is available to systematically identify solution conditions that promote crystallization. To help determine relationships between macromolecular properties and their crystallization propensity, we have trained statistical models on samples for 182 proteins supplied by the Northeast Structural Genomics consortium. Gaussian processes, which capture trends beyond the reach of linear statistical models, distinguish between two main physico-chemical mechanisms driving crystallization. One is characterized by low levels of side chain entropy and has been extensively reported in the literature. The other identifies specific electrostatic interactions not previously described in the crystallization context. Because evidence for two distinct mechanisms can be gleaned both from crystal contacts and from solution conditions leading to successful crystallization, the model offers future avenues for optimizing crystallization screens based on partial structural information. The availability of crystallization data coupled with structural outcomes analyzed through state-of-the-art statistical models may thus guide macromolecular crystallization toward a more rational basis.