917 resultados para complex nonlinear least squares


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Leaders must scan the internal and external environment, chart strategic and task objectives, and provide performance feedback. These instrumental leadership (IL) functions go beyond the motivational and quid-pro quo leader behaviors that comprise the full-range-transformational, transactional, and laissez faire-leadership model. In four studies we examined the construct validity of IL. We found evidence for a four-factor IL model that was highly prototypical of good leadership. IL predicted top-level leader emergence controlling for the full-range factors, initiating structure, and consideration. It also explained unique variance in outcomes beyond the full-range factors; the effects of transformational leadership were vastly overstated when IL was omitted from the model. We discuss the importance of a "fuller full-range" leadership theory for theory and practice. We also showcase our methodological contributions regarding corrections for common method variance (i.e., endogeneity) bias using two-stage least squares (2SLS) regression and Monte Carlo split-sample designs.

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Although the relationship between serum uric acid (SUA) and adiposity is well established, the direction of the causality is still unclear in the presence of conflicting evidences. We used a bidirectional Mendelian randomization approach to explore the nature and direction of causality between SUA and adiposity in a population-based study of Caucasians aged 35 to 75 years. We used, as instrumental variables, rs6855911 within the SUA gene SLC2A9 in one direction, and combinations of SNPs within the adiposity genes FTO, MC4R and TMEM18 in the other direction. Adiposity markers included weight, body mass index, waist circumference and fat mass. We applied a two-stage least squares regression: a regression of SUA/adiposity markers on our instruments in the first stage and a regression of the response of interest on the fitted values from the first stage regression in the second stage. SUA explained by the SLC2A9 instrument was not associated to fat mass (regression coefficient [95% confidence interval]: 0.05 [-0.10, 0.19] for fat mass) contrasting with the ordinary least square estimate (0.37 [0.34, 0.40]). By contrast, fat mass explained by genetic variants of the FTO, MC4R and TMEM18 genes was positively and significantly associated to SUA (0.31 [0.01, 0.62]), similar to the ordinary least square estimate (0.27 [0.25, 0.29]). Results were similar for the other adiposity markers. Using a bidirectional Mendelian randomization approach in adult Caucasians, our findings suggest that elevated SUA is a consequence rather than a cause of adiposity.

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Inconsistencies about dynamic asymmetry between the on- and off-transient responses in VO2 are found in the literature. Therefore the purpose of this study was to examine VO2 on- and off-transients during moderate- and heavy-intensity cycling exercise in trained subjects. Ten men underwent an initial incremental test for the estimation of ventilatory threshold (VT) and, on different days, two bouts of square-wave exercise at moderate (<VT) and heavy (>VT) intensities. VO2 kinetics in exercise and recovery were better described by a single exponential model (<VT), or by a double exponential with two time delays (>VT). For moderate exercise, we found a symmetry of VO2 kinetics between the on- and off-transients (i.e., fundamental component), consistent with a system manifesting linear control dynamics. For heavy exercise, a slow component superimposed on the fundamental phase was expressed in both the exercise and recovery, with similar parameter estimates. But the on-transient values of the time constant were appreciably faster than the associated off-transient, and independent of the work rate imposed (<VT and >VT). Our results do not support a dynamically linear system model of VO2 during cycling exercise in the heavy-intensity domain.

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Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression

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In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

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OBJECTIVE Our objective was to test the efficacy and tolerability of three doses of flutamide (125, 250, and 375 mg) combined with a triphasic oral contraceptive (ethynylestradiol/levonorgestrel) during 12 months to treat moderate to severe hirsutism in patients with polycystic ovary syndrome or idiopathic hirsutism. DESIGN We conducted a randomized, double-blind, placebo-controlled, parallel clinical trial. PATIENTS A total of 131 premenopausal women, suffering from moderate to severe hirsutism, were randomized to placebo or 125, 250, or 375 mg flutamide daily associated with a triphasic oral contraceptive pill. Hirsutism (Ferriman-Gallwey), acne and seborrhea (Cremoncini), and hormone serum levels were monitored at baseline and at 3 (except hormone serum levels), 6, and 12 months. Side effects and biochemical, hematological, and hepatic parameters were assessed. METHODS We used three-way ANOVA (subject, dose, and visit) with Scheffé adjustment for multiple comparisons or nonparametrical Friedman test and least-squares mean (paired data) and Kruskall-Wallis test for unpaired data analyses. We used chi(2) or Fisher's test for categorical data. RESULTS A total of 119 patients were included in the intention-to-treat analysis. All flutamide doses induced a significant decrease in hirsutism, acne, and seborrhea scores after 12 months compared with placebo without differences among dose levels. Similar related side effects were observed with placebo and 125 mg flutamide (12.5%), and slightly higher with 250 mg (17.3%) and 375 mg (21.2%). No statistically significant differences were observed either among doses or compared with placebo. CONCLUSIONS Flutamide at 125 mg daily during 12 months was the minimum effective dose to diminish hirsutism in patients with polycystic ovary syndrome or with idiopathic hirsutism.

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Imaging mass spectrometry (IMS) represents an innovative tool in the cancer research pipeline, which is increasingly being used in clinical and pharmaceutical applications. The unique properties of the technique, especially the amount of data generated, make the handling of data from multiple IMS acquisitions challenging. This work presents a histology-driven IMS approach aiming to identify discriminant lipid signatures from the simultaneous mining of IMS data sets from multiple samples. The feasibility of the developed workflow is evaluated on a set of three human colorectal cancer liver metastasis (CRCLM) tissue sections. Lipid IMS on tissue sections was performed using MALDI-TOF/TOF MS in both negative and positive ionization modes after 1,5-diaminonaphthalene matrix deposition by sublimation. The combination of both positive and negative acquisition results was performed during data mining to simplify the process and interrogate a larger lipidome into a single analysis. To reduce the complexity of the IMS data sets, a sub data set was generated by randomly selecting a fixed number of spectra from a histologically defined region of interest, resulting in a 10-fold data reduction. Principal component analysis confirmed that the molecular selectivity of the regions of interest is maintained after data reduction. Partial least-squares and heat map analyses demonstrated a selective signature of the CRCLM, revealing lipids that are significantly up- and down-regulated in the tumor region. This comprehensive approach is thus of interest for defining disease signatures directly from IMS data sets by the use of combinatory data mining, opening novel routes of investigation for addressing the demands of the clinical setting.

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BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

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Body mass and body condition are often tightly linked to animal health and fitness in the wild and thus are key measures for ecophysiologists and behavioral ecologists. In some animals, such as large seabird species, obtaining indexes of structural size is relatively easy, whereas measuring body mass under specific field circumstances may be more of a challenge. Here, we suggest an alternative, easily measurable, and reliable surrogate of body mass in field studies, that is, body girth. Using 234 free-living king penguins (Aptenodytes patagonicus) at various stages of molt and breeding, we measured body girth under the flippers, body mass, and bill and flipper length. We found that body girth was strongly and positively related to body mass in both molting (R(2) = 0.91) and breeding (R(2) = 0.73) birds, with the mean error around our predictions being 6.4%. Body girth appeared to be a reliable proxy measure of body mass because the relationship did not vary according to year and experimenter, bird sex, or stage within breeding groups. Body girth was, however, a weak proxy of body mass in birds at the end of molt, probably because most of those birds had reached a critical depletion of energy stores. Body condition indexes established from ordinary least squares regressions of either body girth or body mass on structural size were highly correlated (r(s) = 0.91), suggesting that body girth was as good as body mass in establishing body condition indexes in king penguins. Body girth may prove a useful proxy to body mass for estimating body condition in field investigations and could likely provide similar information in other penguins and large animals that may be complicated to weigh in the wild.

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Lisdexamfetamine dimesylate (LDX) is a long-acting, prodrug stimulant therapy for patients with attention-deficit/hyperactivity disorder (ADHD). This randomized placebo-controlled trial of an optimized daily dose of LDX (30, 50 or 70 mg) was conducted in children and adolescents (aged 6-17 years) with ADHD. To evaluate the efficacy of LDX throughout the day, symptoms and behaviors of ADHD were evaluated using an abbreviated version of the Conners' Parent Rating Scale-Revised (CPRS-R) at 1000, 1400 and 1800 hours following early morning dosing (0700 hours). Osmotic-release oral system methylphenidate (OROS-MPH) was included as a reference treatment, but the study was not designed to support a statistical comparison between LDX and OROS-MPH. The full analysis set comprised 317 patients (LDX, n = 104; placebo, n = 106; OROS-MPH, n = 107). At baseline, CPRS-R total scores were similar across treatment groups. At endpoint, differences (active treatment - placebo) in least squares (LS) mean change from baseline CPRS-R total scores were statistically significant (P < 0.001) throughout the day for LDX (effect sizes: 1000 hours, 1.42; 1400 hours, 1.41; 1800 hours, 1.30) and OROS-MPH (effect sizes: 1000 hours, 1.04; 1400 hours, 0.98; 1800 hours, 0.92). Differences in LS mean change from baseline to endpoint were statistically significant (P < 0.001) for both active treatments in all four subscales of the CPRS-R (ADHD index, oppositional, hyperactivity and cognitive). In conclusion, improvements relative to placebo in ADHD-related symptoms and behaviors in children and adolescents receiving a single morning dose of LDX or OROS-MPH were maintained throughout the day and were ongoing at the last measurement in the evening (1800 hours).

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La principal aportación de este trabajo es poner de manifiesto que la capacidad absortiva de las economías cambia en función de si el país es el líder o es un seguidor. Aunque tampoco olvidamos otras variables como son la I+D interna, la I+D externa, el desarrollo del sistema financiero y las instituciones. Para ello, primero se prueba la presencia de una raíz unitaria y después se asegura una relación de cointegración entre las variables implicadas en el modelo para poder sacar conclusiones a largo plazo. Y por último, para estimar el modelo, se utilizará una técnica econométrica que combina el tratamiento tradicional de los datos de panel con las técnicas de cointegración: los Dynamics Ordinary Least Squares (DOLS). Esta técnica soluciona las limitaciones de los OLS, ya que su distribución no suele ser estándar por la presencia de un sesgo de muestras finitas (causado bien por la endogeneidad de las variables explicativas bien por la correlación serial de la perturbación). Utilizando un panel de datos que comprende 8 países de la OECD entre 1973-2004 y para el Business Sector, se encuentran diversos resultados, entre los que destacamos que la I+D interna, la I+D externa, la frontera tecnológica, la capacidad absortiva y el desarrollo de las instituciones tienen un impacto positivo sobre el nivel de la PTF. En cambio, el desarrollo del sistema financiero tiene un impacto negativo. Palabras claves: fuentes de la I+D, frontera tecnológica, capacidad absortiva, raíces unitarias, cointegración, DOLS.

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Na pesquisa aqui relatada, visa-se investigar os antecedentes da intenção de uso de sistemas de home broker sob a ótica dos investidores do mercado acionário. Para atingir esse objetivo, por meio de referencial teórico baseado em teorias de aceitação de sistemas de informação, difusão da inovação, confiança em ambientes virtuais e satisfação do usuário, foi elaborado um modelo teórico e foram propostas hipóteses de pesquisa. Por meio de técnicas de equações estruturais baseadas em Partial Least Squares (PLS), a partir de 152 questionários válidos, coletados via web survey junto a investidores do mercado acionário brasileiro, foram testados o modelo proposto e as hipóteses de pesquisa. Identificaram-se, assim, os fatores compatibilidade, utilidade percebida e facilidade de uso percebida como antecedentes estatisticamente significantes do fator satisfação do usuário com o sistema de home broker, o qual, por sua vez, teve efeito estatisticamente significante na intenção de uso do sistema. São apresentadas, ainda, as implicações acadêmicas e gerenciais do trabalho, assim como suas limitações e uma agenda de pesquisa para essa importante área do conhecimento.

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Accumulation of fat in the liver increases the risk to develop fibrosis and cirrhosis and is associated with development of the metabolic syndrome. Here, to identify genes or gene pathways that may underlie the genetic susceptibility to fat accumulation in liver, we studied A/J and C57Bl/6 mice that are resistant and sensitive to diet-induced hepatosteatosis and obesity, respectively. We performed comparative transcriptomic and lipidomic analysis of the livers of both strains of mice fed a high fat diet for 2, 10, and 30 days. We found that resistance to steatosis in A/J mice was associated with the following: (i) a coordinated up-regulation of 10 genes controlling peroxisome biogenesis and β-oxidation; (ii) an increased expression of the elongase Elovl5 and desaturases Fads1 and Fads2. In agreement with these observations, peroxisomal β-oxidation was increased in livers of A/J mice, and lipidomic analysis showed increased concentrations of long chain fatty acid-containing triglycerides, arachidonic acid-containing lysophosphatidylcholine, and 2-arachidonylglycerol, a cannabinoid receptor agonist. We found that the anti-inflammatory CB2 receptor was the main hepatic cannabinoid receptor, which was highly expressed in Kupffer cells. We further found that A/J mice had a lower pro-inflammatory state as determined by lower plasma levels and IL-1β and granulocyte-CSF and reduced hepatic expression of their mRNAs, which were found only in Kupffer cells. This suggests that increased 2-arachidonylglycerol production may limit Kupffer cell activity. Collectively, our data suggest that genetic variations in the expression of peroxisomal β-oxidation genes and of genes controlling the production of an anti-inflammatory lipid may underlie the differential susceptibility to diet-induced hepatic steatosis and pro-inflammatory state.

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Geoelectrical techniques are widely used to monitor groundwater processes, while surprisingly few studies have considered audio (AMT) and radio (RMT) magnetotellurics for such purposes. In this numerical investigation, we analyze to what extent inversion results based on AMT and RMT monitoring data can be improved by (1) time-lapse difference inversion; (2) incorporation of statistical information about the expected model update (i.e., the model regularization is based on a geostatistical model); (3) using alternative model norms to quantify temporal changes (i.e., approximations of l(1) and Cauchy norms using iteratively reweighted least-squares), (4) constraining model updates to predefined ranges (i.e., using Lagrange Multipliers to only allow either increases or decreases of electrical resistivity with respect to background conditions). To do so, we consider a simple illustrative model and a more realistic test case related to seawater intrusion. The results are encouraging and show significant improvements when using time-lapse difference inversion with non l(2) model norms. Artifacts that may arise when imposing compactness of regions with temporal changes can be suppressed through inequality constraints to yield models without oscillations outside the true region of temporal changes. Based on these results, we recommend approximate l(1)-norm solutions as they can resolve both sharp and smooth interfaces within the same model. (C) 2012 Elsevier B.V. All rights reserved.

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The Maximum Capture problem (MAXCAP) is a decision model that addresses the issue of location in a competitive environment. This paper presents a new approach to determine which store s attributes (other than distance) should be included in the newMarket Capture Models and how they ought to be reflected using the Multiplicative Competitive Interaction model. The methodology involves the design and development of a survey; and the application of factor analysis and ordinary least squares. Themethodology has been applied to the supermarket sector in two different scenarios: Milton Keynes (Great Britain) and Barcelona (Spain).