932 resultados para Linear and multilinear programming


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The life history of the fruit fly (Drosophila melanogaster) is well understood, but fitness components are rarely measured by following single individuals over their lifetime, thereby limiting insights into lifetime reproductive success, reproductive senescence and post-reproductive lifespan. Moreover, most studies have examined long-established laboratory strains rather than freshly caught individuals and may thus be confounded by adaptation to laboratory culture, inbreeding or mutation accumulation. Here, we have followed the life histories of individual females from three recently caught, non-laboratory-adapted wild populations of D. melanogaster. Populations varied in a number of life-history traits, including ovariole number, fecundity, hatchability and lifespan. To describe individual patterns of age-specific fecundity, we developed a new model that allowed us to distinguish four phases during a female's life: a phase of reproductive maturation, followed by a period of linear and then exponential decline in fecundity and, finally, a post-ovipository period. Individual females exhibited clear-cut fecundity peaks, which contrasts with previous analyses, and post-peak levels of fecundity declined independently of how long females lived. Notably, females had a pronounced post-reproductive lifespan, which on average made up 40% of total lifespan. Post-reproductive lifespan did not differ among populations and was not correlated with reproductive fitness components, supporting the hypothesis that this period is a highly variable, random 'add-on' at the end of reproductive life rather than a correlate of selection on reproductive fitness. Most life-history traits were positively correlated, a pattern that might be due to genotype by environment interactions when wild flies are brought into a novel laboratory environment but that is unlikely explained by inbreeding or positive mutational covariance caused by mutation accumulation.

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Introduction: The SMILING project, a multicentric project fundedby the European Union, aims to develop a new gait and balance trainingprogram to prevent falls in older persons. The program includes the"SMILING shoe", an innovative device that generates mechanical perturbationwhile walking by changing the soles' inclination. Induced perturbationschallenge subjects' balance and force them to react to avoidfalls. By training specifically the complex motor reactions used to maintainbalance when walking on irregular ground, the program will improvesubjects' ability to react in situation of unsteadiness and reduce theirrisk of falling. Methods: The program will be evaluated in a multicentric,cross-over randomized controlled trial. Overall, 112 subjects (aged≥65 years, ≥1 falls, POMA score 22-26/28) will be enrolled. Subjectswill be randomised in 2 groups: group A begin the training with active"SMILING shoes", group B with inactive dummy shoes. After 4 weeksof training, group A and B will exchange the shoes. Supervised trainingsessions (30 minutes twice a week for 8 weeks) include walkingtasks of progressive difficulties.To avoid a learning effect, "SMILINGshoes" perturbations will be generated in a non-linear and chaotic way.Gait performance, fear of falling, and acceptability of the program willbe assessed. Conclusion: The SMILING program is an innovative interventionfor falls prevention in older persons based on gait and balancetraining using chaotic perturbations. Because of the easy use of the"SMILING shoes", this program could be used in various settings, suchas geriatric clinics or at home.

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BACKGROUND: The aim of this study was to assess the pharmacology, toxicity and activity of high-dose ifosfamide mesna +/- GM-CSF administered by a five-day continuous infusion at a total ifosfamide dose of 12-18 g/m2 in adult patients with advanced sarcomas. PATIENTS AND METHODS: Between January 1991 and October 1992 32 patients with advanced or metastatic sarcoma were entered the study. Twenty-seven patients were pretreated including twenty-three with prior ifosfamide at less than 8 g/m2 total dose/cycle. In 25 patients (27 cycles) extensive pharmacokinetic analyses were performed. RESULTS: The area under the plasma concentration-time curve (AUC) for ifosfamide increased linearly with dose while the AUC's of the metabolites measured in plasma by thin-layer chromatography did not increase with dose, particularly that of the active metabolite isophosphoramide mustard. Furthermore the AUC of the inactive carboxymetabolite did not increase with dose. Interpatient variability of pharmacokinetic parameters was high. Dose-limiting toxicity was myelosuppression at 18 g/m2 total dose with grade 4 neutropenia in five of six patients and grade 4 thrombocytopenia in four of six patients. Therefore the maximum tolerated dose was considered to be 18 g/m2 total dose. There was one CR and eleven PR in twenty-nine evaluable patients (overall response rate 41%). CONCLUSION: Both the activation and inactivation pathways of ifosfamide are non-linear and saturable at high-doses although the pharmacokinetics of the parent drug itself are dose linear. Ifosfamide doses greater than 14-16 g/m2 per cycle appear to result in a relative decrease of the active metabolite isophosphoramide mustard. These data suggest a dose-dependent saturation or even inhibition of ifosfamide metabolism by increasing high dose ifosfamide and suggest the need for further metabolic studies.

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BACKGROUND AND OBJECTIVES: The estimated GFR (eGFR) is important in clinical practice. To find the best formula for eGFR, this study assessed the best model of correlation between sinistrin clearance (iGFR) and the solely or combined cystatin C (CysC)- and serum creatinine (SCreat)-derived models. It also evaluated the accuracy of the combined Schwartz formula across all GFR levels. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Two hundred thirty-eight iGFRs performed between January 2012 and April 2013 for 238 children were analyzed. Regression techniques were used to fit the different equations used for eGFR (i.e., logarithmic, inverse, linear, and quadratic). The performance of each model was evaluated using the Cohen κ correlation coefficient and the percentage reaching 30% accuracy was calculated. RESULTS: The best model of correlation between iGFRs and CysC is linear; however, it presents a low κ coefficient (0.24) and is far below the Kidney Disease Outcomes Quality Initiative targets to be validated, with only 84% of eGFRs reaching accuracy of 30%. SCreat and iGFRs showed the best correlation in a fitted quadratic model with a κ coefficient of 0.53 and 93% accuracy. Adding CysC significantly (P<0.001) increased the κ coefficient to 0.56 and the quadratic model accuracy to 97%. Therefore, a combined SCreat and CysC quadratic formula was derived and internally validated using the cross-validation technique. This quadratic formula significantly outperformed the combined Schwartz formula, which was biased for an iGFR≥91 ml/min per 1.73 m(2). CONCLUSIONS: This study allowed deriving a new combined SCreat and CysC quadratic formula that could replace the combined Schwartz formula, which is accurate only for children with moderate chronic kidney disease.

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We have developed a processing methodology that allows crosshole ERT (electrical resistivity tomography) monitoring data to be used to derive temporal fluctuations of groundwater electrical resistivity and thereby characterize the dynamics of groundwater in a gravel aquifer as it is infiltrated by river water. Temporal variations of the raw ERT apparent-resistivity data were mainly sensitive to the resistivity (salinity), temperature and height of the groundwater, with the relative contributions of these effects depending on the time and the electrode configuration. To resolve the changes in groundwater resistivity, we first expressed fluctuations of temperature-detrended apparent-resistivity data as linear superpositions of (i) time series of riverwater-resistivity variations convolved with suitable filter functions and (ii) linear and quadratic representations of river-water-height variations multiplied by appropriate sensitivity factors; river-water height was determined to be a reliable proxy for groundwater height. Individual filter functions and sensitivity factors were obtained for each electrode configuration via deconvolution using a one month calibration period and then the predicted contributions related to changes in water height were removed prior to inversion of the temperature-detrended apparent-resistivity data. Applications of the filter functions and sensitivity factors accurately predicted the apparent-resistivity variations (the correlation coefficient was 0.98). Furthermore, the filtered ERT monitoring data and resultant time-lapse resistivity models correlated closely with independently measured groundwater electrical resistivity monitoring data and only weakly with the groundwater-height fluctuations. The inversion results based on the filtered ERT data also showed significantly less inversion artefacts than the raw data inversions. We observed resistivity increases of up to 10% and the arrival time peaks in the time-lapse resistivity models matched those in the groundwater resistivity monitoring data.

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Soil moisture is the property which most greatly influences the soil dielectric constant, which is also influenced by soil mineralogy. The aim of this study was to determine mathematical models for soil moisture and the dielectric constant (Ka) for a Hapludalf, two clayey Hapludox and a very clayey Hapludox and test the reliability of universal models, such as those proposed by Topp and Ledieu and their co-workers in the 80's, and specific models to estimate soil moisture with a TDR. Soil samples were collected from the 0 to 0.30 m layer, sieved through a mesh of 0.002 m diameter and packed in PVC cylinders with a 0.1 m diameter and 0.3 m height. Seven samples of each soil class were saturated by capillarity and a probe composed of two rods was inserted in each one of them. Moisture readings began with the saturated soil and concluded when the soil was near permanent wilting point. In each step, the samples were weighed on a precision scale to calculate volumetric moisture. Linear and polynomial models were adjusted for each soil class and for all soils together between soil moisture and the dielectric constant. Accuracy of the models was evaluated by the coefficient of determination, the standard error of estimate and the 1:1 line. The models proposed by Topp and Ledieu and their co-workers were not adequate for estimating the moisture in the soil classes studied. The adjusted linear and polynomial models for the entire set of data of the four soil classes did not have sufficient accuracy for estimating soil moisture. The greater the soil clay and Fe oxide content, the greater the dielectric constant of the medium for a given volumetric moisture. The specific models, θ = 0.40283 - 0.04231 Ka + 0.00194 Ka² - 0.000022 Ka³ (Hapludox) θ = 0.01971 + 0.02902 Ka - 0.00086 Ka² + 0.000012 Ka³ (Hapludox -PF), θ = 0.01692 - 0.00507 Ka (Hapludalf) and θ = 0.08471 + 0.01145 Ka (Hapludox-CA), show greater accuracy and reliability for estimating soil moisture in the soil classes studied.

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The Cerrado (Brazilian Savannah) plays an important economic and financial role in the nation, since the pastures of this biome feed cattle for half of the domestic bovine meat productivity, and its agricultural fields produce a third of the country's grain. The variability and spatial dependence between the soil physical attributes and soybean yield were evaluated in a crop rotation planted on a degraded brachiaria pasture, on a dystroferric Red Latosol of an experimental farm of the State University of São Paulo (UNESP), in the 2005/2006 growing season. The linear and spatial correlations between these attributes were also studied, to determine conditions that would allow increased agricultural productivity. In the above pasture area, a grid was installed with 124 plots, spaced 10.0 x 10.0 m and 5.0 x 5.0 m apart, in a total area of 7,500 m². From the linear and spatial point of view, the high grain yield can be explained by the number of grains per plant and soil macroporosity. The high variability observed for most soil properties indicated that the crop - livestock integration system results in environmental heterogeneity of the soil.

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BACKGROUND: Strategies to dissect phenotypic and genetic heterogeneity of major depressive disorder (MDD) have mainly relied on subphenotypes, such as age at onset (AAO) and recurrence/episodicity. Yet, evidence on whether these subphenotypes are familial or heritable is scarce. The aims of this study are to investigate the familiality of AAO and episode frequency in MDD and to assess the proportion of their variance explained by common single nucleotide polymorphisms (SNP heritability). METHOD: For investigating familiality, we used 691 families with 2-5 full siblings with recurrent MDD from the DeNt study. We fitted (square root) AAO and episode count in a linear and a negative binomial mixed model, respectively, with family as random effect and adjusting for sex, age and center. The strength of familiality was assessed with intraclass correlation coefficients (ICC). For estimating SNP heritabilities, we used 3468 unrelated MDD cases from the RADIANT and GSK Munich studies. After similarly adjusting for covariates, derived residuals were used with the GREML method in GCTA (genome-wide complex trait analysis) software. RESULTS: Significant familial clustering was found for both AAO (ICC = 0.28) and episodicity (ICC = 0.07). We calculated from respective ICC estimates the maximal additive heritability of AAO (0.56) and episodicity (0.15). SNP heritability of AAO was 0.17 (p = 0.04); analysis was underpowered for calculating SNP heritability of episodicity. CONCLUSIONS: AAO and episodicity aggregate in families to a moderate and small degree, respectively. AAO is under stronger additive genetic control than episodicity. Larger samples are needed to calculate the SNP heritability of episodicity. The described statistical framework could be useful in future analyses.

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A Lagrangian treatment of the quantization of first class Hamiltonian systems with constraints and Hamiltonian linear and quadratic in the momenta, respectively, is performed. The first reduce and then quantize and the first quantize and then reduce (Diracs) methods are compared. A source of ambiguities in this latter approach is pointed out and its relevance on issues concerning self-consistency and equivalence with the first reduce method is emphasized. One of the main results is the relation between the propagator obtained la Dirac and the propagator in the full space. As an application of the formalism developed, quantization on coset spaces of compact Lie groups is presented. In this case it is shown that a natural selection of a Dirac quantization allows for full self-consistency and equivalence. Finally, the specific case of the propagator on a two-dimensional sphere S2 viewed as the coset space SU(2)/U(1) is worked out. 1995 American Institute of Physics.

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Brazilian soils have natural high chemical variability; thus, apparent electrical conductivity (ECa) can assist interpretation of crop yield variations. We aimed to select soil chemical properties with the best linear and spatial correlations to explain ECa variation in the soil using a Profiler sensor (EMP-400). The study was carried out in Sidrolândia, MS, Brazil. We analyzed the following variables: electrical conductivity - EC (2, 7, and 15 kHz), organic matter, available K, base saturation, and cation exchange capacity (CEC). Soil ECa was measured with the aid of an all-terrain vehicle, which crossed the entire area in strips spaced at 0.45 m. Soil samples were collected at the 0-20 cm depth with a total of 36 samples within about 70 ha. Classical descriptive analysis was applied to each property via SAS software, and GS+ for spatial dependence analysis. The equipment was able to simultaneously detect ECa at the different frequencies. It was also possible to establish site-specific management zones through analysis of correlation with chemical properties. We observed that CEC was the property that had the best correlation with ECa at 15 kHz.

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Work-related flow is defined as a sudden and enjoyable merging of action and awareness that represents a peak experience in the daily lives of workers. Employees" perceptions of challenge and skill and their subjective experiences in terms of enjoyment, interest and absorption were measured using the experience sampling method, yielding a total of 6981 observations from a sample of 60 employees. Linear and nonlinear approaches were applied in order to model both continuous and sudden changes. According to the R2, AICc and BIC indexes, the nonlinear dynamical systems model (i.e. cusp catastrophe model) fit the data better than the linear and logistic regression models. Likewise, the cusp catastrophe model appears to be especially powerful for modelling those cases of high levels of flow. Overall, flow represents a nonequilibrium condition that combines continuous and abrupt changes across time. Research and intervention efforts concerned with this process should focus on the variable of challenge, which, according to our study, appears to play a key role in the abrupt changes observed in work-related flow.

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Purpose: Polyethylene wear is a recurrent problem in joint arthroplasty. Small debris particles are also associated to inflammation reaction of the surrounding bone, eventually leading to the failure of the bound between the implant and the host bone, and implant loosening. The goal of this study was thus to estimate the volume of polyethylene wear of a reversed prosthesis, and compare it to an anatomic prosthesis, during one year of activities of daily living. Material and Methods: A numerical musculoskeletal model of the glenohumeral joint was used for this comparative study. The reversed (RP) and anatomic (AP) Aequalis prostheses were positioned in the numerical model. Eight levels of abduction were considered. Their daily frequency was estimated from in-vivo recorded data on healthy volunteers during activities of daily living. One year of use was simulated to predict the linear and volumetric wear. The volumetric wear was the difference of volume between the original and worn component. Results: With the AP, the contact pattern on the glenoid surface moved rapidly from the inferior to the superior side during the first 30 degrees of abduction, and then went back to the inferior side. With the RP, the contact pattern on the humeral cup surface remained at the inferior side. Contact pressure was 20 times lower with the RP than with the AP. One year of use produced a maximum linear wear of 0.2 mm with the AP, and 0.13 mm with the RP. However, the volumetric wear was 8.4 mm3 with the AP, but reached 44.6 mm3 with the RP. Conclusion: Polyethylene particles are a matter of concern with AP. Infiltration of these particles within the bone-implant interface can induce a implant loosening. This problem should not be underestimated with RP. It might be associated to a higher level of humeral stem loosening reported with RP. The long term survival of RP might be improved by using a highly cross-linked polyethylene, which has a better abrasion resistance but lower plastic resistance.

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We consider the numerical treatment of the optical flow problem by evaluating the performance of the trust region method versus the line search method. To the best of our knowledge, the trust region method is studied here for the first time for variational optical flow computation. Four different optical flow models are used to test the performance of the proposed algorithm combining linear and nonlinear data terms with quadratic and TV regularization. We show that trust region often performs better than line search; especially in the presence of non-linearity and non-convexity in the model.

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Global positioning systems (GPS) offer a cost-effective and efficient method to input and update transportation data. The spatial location of objects provided by GPS is easily integrated into geographic information systems (GIS). The storage, manipulation, and analysis of spatial data are also relatively simple in a GIS. However, many data storage and reporting methods at transportation agencies rely on linear referencing methods (LRMs); consequently, GPS data must be able to link with linear referencing. Unfortunately, the two systems are fundamentally incompatible in the way data are collected, integrated, and manipulated. In order for the spatial data collected using GPS to be integrated into a linear referencing system or shared among LRMs, a number of issues need to be addressed. This report documents and evaluates several of those issues and offers recommendations. In order to evaluate the issues associated with integrating GPS data with a LRM, a pilot study was created. To perform the pilot study, point features, a linear datum, and a spatial representation of a LRM were created for six test roadway segments that were located within the boundaries of the pilot study conducted by the Iowa Department of Transportation linear referencing system project team. Various issues in integrating point features with a LRM or between LRMs are discussed and recommendations provided. The accuracy of the GPS is discussed, including issues such as point features mapping to the wrong segment. Another topic is the loss of spatial information that occurs when a three-dimensional or two-dimensional spatial point feature is converted to a one-dimensional representation on a LRM. Recommendations such as storing point features as spatial objects if necessary or preserving information such as coordinates and elevation are suggested. The lack of spatial accuracy characteristic of most cartography, on which LRM are often based, is another topic discussed. The associated issues include linear and horizontal offset error. The final topic discussed is some of the issues in transferring point feature data between LRMs.

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The Mechanistic-Empirical Pavement Design Guide (MEPDG) was developed under National Cooperative Highway Research Program (NCHRP) Project 1-37A as a novel mechanistic-empirical procedure for the analysis and design of pavements. The MEPDG was subsequently supported by AASHTO’s DARWin-ME and most recently marketed as AASHTOWare Pavement ME Design software as of February 2013. Although the core design process and computational engine have remained the same over the years, some enhancements to the pavement performance prediction models have been implemented along with other documented changes as the MEPDG transitioned to AASHTOWare Pavement ME Design software. Preliminary studies were carried out to determine possible differences between AASHTOWare Pavement ME Design, MEPDG (version 1.1), and DARWin-ME (version 1.1) performance predictions for new jointed plain concrete pavement (JPCP), new hot mix asphalt (HMA), and HMA over JPCP systems. Differences were indeed observed between the pavement performance predictions produced by these different software versions. Further investigation was needed to verify these differences and to evaluate whether identified local calibration factors from the latest MEPDG (version 1.1) were acceptable for use with the latest version (version 2.1.24) of AASHTOWare Pavement ME Design at the time this research was conducted. Therefore, the primary objective of this research was to examine AASHTOWare Pavement ME Design performance predictions using previously identified MEPDG calibration factors (through InTrans Project 11-401) and, if needed, refine the local calibration coefficients of AASHTOWare Pavement ME Design pavement performance predictions for Iowa pavement systems using linear and nonlinear optimization procedures. A total of 130 representative sections across Iowa consisting of JPCP, new HMA, and HMA over JPCP sections were used. The local calibration results of AASHTOWare Pavement ME Design are presented and compared with national and locally calibrated MEPDG models.