939 resultados para Individual-based modeling


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Transparency document related to this article can be found online at http://dx.doi.org/10.1016/j.bbrc.2015.10.014

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This document is a report prepared for the DG for Employment and Social Affairs of the European Commission. It surveys the available evidence on the contribution of investment in human capital to aggregate productivity growth and on its impact on wages and other labour outcomes at the individual level. It also draws some tentative policy conclusions for an average European country.

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Export activities are a major source of economic growth and are considered important both at the national level and for individual businesses. Moreover, in the case of SMEs, they gain particular relevance, exporting being the most common foreign market entry mode for these firms. The decision maker’s role in the export activity is crucial, particularly in the case of SMEs. However, the extant literature on internationalization is characterized by a lack of consensus among scholars as to what constitutes the managerial factor in determining exporting. Therefore, this study focuses on the following issue: Which are the decision maker’s characteristics and perceptions that may influence the export behaviour of Catalan SMEs? To address this question a multiple case study method is applied across four Catalan exporting SMEs. The methodology chosen for analysing the empirical data is relying on the proposition testing approach while the investigation is conducted including both within and cross-case analysis. The findings show that high educational level, language skills, high risk tolerance, innovativeness as well as strongly perceived export stimuli as compared to low and easy to overcome export barriers positively influence the export involvement and development of SMEs. The study provides further insights into the research topic by jointly studying managerial characteristics and perceptions. Additionally, the majority of research on exporting topics has been carried out in the USA, so there is a clear need of investigation in the field in other countries, moreover in Spain where the exporting activities have not been as widely studied.

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Ornament expression fluctuates with age in many organisms. Whether these changes are adaptively plastic is poorly known. In order to understand the ultimate function of melanin-based ornaments, we studied their within-individual fluctuations and their covariation with fitness-related traits. In barn owls (Tyto alba), individuals vary from reddish-brown pheomelanic to white and from immaculate to marked with black eumelanic spots, males being less reddish and less spotted than females. During the first molt, both sexes became less pheomelanic, females displayed larger spots and males fewer spots, but the extent of these changes was not associated with reproduction. At subsequent molts, intra-individual changes in melanin-based traits covaried with simultaneous reproduction changes. Adult females bred earlier in the season and laid larger eggs when they became scattered with larger spots, while adults of both sexes produced larger broods when they became whiter. These results suggest that the production of melanin pigments and fitness-related life history traits are concomitantly regulated in a sex-specific way.

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Among the largest resources for biological sequence data is the large amount of expressed sequence tags (ESTs) available in public and proprietary databases. ESTs provide information on transcripts but for technical reasons they often contain sequencing errors. Therefore, when analyzing EST sequences computationally, such errors must be taken into account. Earlier attempts to model error prone coding regions have shown good performance in detecting and predicting these while correcting sequencing errors using codon usage frequencies. In the research presented here, we improve the detection of translation start and stop sites by integrating a more complex mRNA model with codon usage bias based error correction into one hidden Markov model (HMM), thus generalizing this error correction approach to more complex HMMs. We show that our method maintains the performance in detecting coding sequences.

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Introduction: Non-invasive brain imaging techniques often contrast experimental conditions across a cohort of participants, obfuscating distinctions in individual performance and brain mechanisms that are better characterised by the inter-trial variability. To overcome such limitations, we developed topographic analysis methods for single-trial EEG data [1]. So far this was typically based on time-frequency analysis of single-electrode data or single independent components. The method's efficacy is demonstrated for event-related responses to environmental sounds, hitherto studied at an average event-related potential (ERP) level. Methods: Nine healthy subjects participated to the experiment. Auditory meaningful sounds of common objects were used for a target detection task [2]. On each block, subjects were asked to discriminate target sounds, which were living or man-made auditory objects. Continuous 64-channel EEG was acquired during the task. Two datasets were considered for each subject including single-trial of the two conditions, living and man-made. The analysis comprised two steps. In the first part, a mixture of Gaussians analysis [3] provided representative topographies for each subject. In the second step, conditional probabilities for each Gaussian provided statistical inference on the structure of these topographies across trials, time, and experimental conditions. Similar analysis was conducted at group-level. Results: Results show that the occurrence of each map is structured in time and consistent across trials both at the single-subject and at group level. Conducting separate analyses of ERPs at single-subject and group levels, we could quantify the consistency of identified topographies and their time course of activation within and across participants as well as experimental conditions. A general agreement was found with previous analysis at average ERP level. Conclusions: This novel approach to single-trial analysis promises to have impact on several domains. In clinical research, it gives the possibility to statistically evaluate single-subject data, an essential tool for analysing patients with specific deficits and impairments and their deviation from normative standards. In cognitive neuroscience, it provides a novel tool for understanding behaviour and brain activity interdependencies at both single-subject and at group levels. In basic neurophysiology, it provides a new representation of ERPs and promises to cast light on the mechanisms of its generation and inter-individual variability.

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The Mont Collon mafic complex is one of the best preserved examples of the Early Permian magmatism in the Central Alps, related to the intra-continental collapse of the Variscan belt. It mostly consists (> 95 vol.%) of ol+hy-nonnative plagioclase-wehrlites, olivine- and cpx-gabbros with cumulitic structures, crosscut by acid dikes. Pegmatitic gabbros, troctolites and anorthosites outcrop locally. A well-preserved cumulative, sequence is exposed in the Dents de Bertol area (center of intrusion). PT-calculations indicate that this layered magma chamber emplaced at mid-crustal levels at about 0.5 GPa and 1100 degrees C. The Mont Collon cumulitic rocks record little magmatic differentiation, as illustrated by the restricted range of clinopyroxene mg-number (Mg#(cpx)=83-89). Whole-rock incompatible trace-element contents (e.g. Nb, Zr, Ba) vary largely and without correlation with major-element composition. These features are characteristic of an in-situ crystallization process with variable amounts of interstitial liquid L trapped between the cumulus mineral phases. LA-ICPMS measurements show that trace-element distribution in the latter is homogeneous, pointing to subsolidus re-equilibration between crystals and interstitial melts. A quantitative modeling based on Langmuir's in-situ crystallization equation successfully duplicated the REE concentrations in cumulitic minerals of all rock facies of the intrusion. The calculated amounts of interstitial liquid L vary between 0 and 35% for degrees of differentiation F of 0 to 20%, relative to the least evolved facies of the intrusion. L values are well correlated with the modal proportions of interstitial amphibole and whole-rock incompatible trace-element concentrations (e.g. Zr, Nb) of the tested samples. However, the in-situ crystallization model reaches its limitations with rock containing high modal content of REE-bearing minerals (i.e. zircon), such as pegmatitic gabbros. Dikes of anorthositic composition, locally crosscutting the layered lithologies, evidence that the Mont Collon rocks evolved in open system with mixing of intercumulus liquids of different origins and possibly contrasting compositions. The proposed model is not able to resolve these complex open systems, but migrating liquids could be partly responsible for the observed dispersion of points in some correlation diagrams. Absence of significant differentiation with recurrent lithologies in the cumulitic pile of Dents de Bertol points to an efficiently convective magma chamber, with possible periodic replenishment, (c) 2005 Elsevier B.V. All rights reserved.

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The goal of the present work was assess the feasibility of using a pseudo-inverse and null-space optimization approach in the modeling of the shoulder biomechanics. The method was applied to a simplified musculoskeletal shoulder model. The mechanical system consisted in the arm, and the external forces were the arm weight, 6 scapulo-humeral muscles and the reaction at the glenohumeral joint, which was considered as a spherical joint. The muscle wrapping was considered around the humeral head assumed spherical. The dynamical equations were solved in a Lagrangian approach. The mathematical redundancy of the mechanical system was solved in two steps: a pseudo-inverse optimization to minimize the square of the muscle stress and a null-space optimization to restrict the muscle force to physiological limits. Several movements were simulated. The mathematical and numerical aspects of the constrained redundancy problem were efficiently solved by the proposed method. The prediction of muscle moment arms was consistent with cadaveric measurements and the joint reaction force was consistent with in vivo measurements. This preliminary work demonstrated that the developed algorithm has a great potential for more complex musculoskeletal modeling of the shoulder joint. In particular it could be further applied to a non-spherical joint model, allowing for the natural translation of the humeral head in the glenoid fossa.

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The aim of this study is to quantify the prevalence and types of rare chromosome abnormalities (RCAs) in Europe for 2000-2006 inclusive, and to describe prenatal diagnosis rates and pregnancy outcome. Data held by the European Surveillance of Congenital Anomalies database were analysed on all the cases from 16 population-based registries in 11 European countries diagnosed prenatally or before 1 year of age, and delivered between 2000 and 2006. Cases were all unbalanced chromosome abnormalities and included live births, fetal deaths from 20 weeks gestation and terminations of pregnancy for fetal anomaly. There were 10,323 cases with a chromosome abnormality, giving a total birth prevalence rate of 43.8/10,000 births. Of these, 7335 cases had trisomy 21,18 or 13, giving individual prevalence rates of 23.0, 5.9 and 2.3/10,000 births, respectively (53, 13 and 5% of all reported chromosome errors, respectively). In all, 473 cases (5%) had a sex chromosome trisomy, and 778 (8%) had 45,X, giving prevalence rates of 2.0 and 3.3/10,000 births, respectively. There were 1,737 RCA cases (17%), giving a prevalence of 7.4/10,000 births. These included triploidy, other trisomies, marker chromosomes, unbalanced translocations, deletions and duplications. There was a wide variation between the registers in both the overall prenatal diagnosis rate of RCA, an average of 65% (range 5-92%) and the prevalence of RCA (range 2.4-12.9/10,000 births). In all, 49% were liveborn. The data provide the prevalence of families currently requiring specialised genetic counselling services in the perinatal period for these conditions and, for some, long-term care.

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Besides CYP2B6, other polymorphic enzymes contribute to efavirenz (EFV) interindividual variability. This study was aimed at quantifying the impact of multiple alleles on EFV disposition. Plasma samples from 169 human immunodeficiency virus (HIV) patients characterized for CYP2B6, CYP2A6, and CYP3A4/5 allelic diversity were used to build up a population pharmacokinetic model using NONMEM (non-linear mixed effects modeling), the aim being to seek a general approach combining genetic and demographic covariates. Average clearance (CL) was 11.3 l/h with a 65% interindividual variability that was explained largely by CYP2B6 genetic variation (31%). CYP2A6 and CYP3A4 had a prominent influence on CL, mostly when CYP2B6 was impaired. Pharmacogenetics fully accounted for ethnicity, leaving body weight as the only significant demographic factor influencing CL. Square roots of the numbers of functional alleles best described the influence of each gene, without interaction. Functional genetic variations in both principal and accessory metabolic pathways demonstrate a joint impact on EFV disposition. Therefore, dosage adjustment in accordance with the type of polymorphism (CYP2B6, CYP2A6, or CYP3A4) is required in order to maintain EFV within the therapeutic target levels.

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In recent years, multi-atlas fusion methods have gainedsignificant attention in medical image segmentation. Inthis paper, we propose a general Markov Random Field(MRF) based framework that can perform edge-preservingsmoothing of the labels at the time of fusing the labelsitself. More specifically, we formulate the label fusionproblem with MRF-based neighborhood priors, as an energyminimization problem containing a unary data term and apairwise smoothness term. We present how the existingfusion methods like majority voting, global weightedvoting and local weighted voting methods can be reframedto profit from the proposed framework, for generatingmore accurate segmentations as well as more contiguoussegmentations by getting rid of holes and islands. Theproposed framework is evaluated for segmenting lymphnodes in 3D head and neck CT images. A comparison ofvarious fusion algorithms is also presented.

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BACKGROUND: Recommended oral voriconazole (VRC) doses are lower than intravenous doses. Because plasma concentrations impact efficacy and safety of therapy, optimizing individual drug exposure may improve these outcomes. METHODS: A population pharmacokinetic analysis (NONMEM) was performed on 505 plasma concentration measurements involving 55 patients with invasive mycoses who received recommended VRC doses. RESULTS: A 1-compartment model with first-order absorption and elimination best fitted the data. VRC clearance was 5.2 L/h, the volume of distribution was 92 L, the absorption rate constant was 1.1 hour(-1), and oral bioavailability was 0.63. Severe cholestasis decreased VRC elimination by 52%. A large interpatient variability was observed on clearance (coefficient of variation [CV], 40%) and bioavailability (CV 84%), and an interoccasion variability was observed on bioavailability (CV, 93%). Lack of response to therapy occurred in 12 of 55 patients (22%), and grade 3 neurotoxicity occurred in 5 of 55 patients (9%). A logistic multivariate regression analysis revealed an independent association between VRC trough concentrations and probability of response or neurotoxicity by identifying a therapeutic range of 1.5 mg/L (>85% probability of response) to 4.5 mg/L (<15% probability of neurotoxicity). Population-based simulations with the recommended 200 mg oral or 300 mg intravenous twice-daily regimens predicted probabilities of 49% and 87%, respectively, for achievement of 1.5 mg/L and of 8% and 37%, respectively, for achievement of 4.5 mg/L. With 300-400 mg twice-daily oral doses and 200-300 mg twice-daily intravenous doses, the predicted probabilities of achieving the lower target concentration were 68%-78% for the oral regimen and 70%-87% for the intravenous regimen, and the predicted probabilities of achieving the upper target concentration were 19%-29% for the oral regimen and 18%-37% for the intravenous regimen. CONCLUSIONS: Higher oral than intravenous VRC doses, followed by individualized adjustments based on measured plasma concentrations, improve achievement of the therapeutic target that maximizes the probability of therapeutic response and minimizes the probability of neurotoxicity. These findings challenge dose recommendations for VRC.

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This paper discusses how to identify individual-specific causal effects of an ordered discrete endogenous variable. The counterfactual heterogeneous causal information is recovered by identifying the partial differences of a structural relation. The proposed refutable nonparametric local restrictions exploit the fact that the pattern of endogeneity may vary across the level of the unobserved variable. The restrictions adopted in this paper impose a sense of order to an unordered binary endogeneous variable. This allows for a uni.ed structural approach to studying various treatment effects when self-selection on unobservables is present. The usefulness of the identi.cation results is illustrated using the data on the Vietnam-era veterans. The empirical findings reveal that when other observable characteristics are identical, military service had positive impacts for individuals with low (unobservable) earnings potential, while it had negative impacts for those with high earnings potential. This heterogeneity would not be detected by average effects which would underestimate the actual effects because different signs would be cancelled out. This partial identification result can be used to test homogeneity in response. When homogeneity is rejected, many parameters based on averages may deliver misleading information.

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In this analysis, we examine the relationship between an individual's decision to volunteer and the average level of volunteering in the community where the individual resides. Our theoretical model is based on a coordination game , in which volunteering by others is informative regarding the benefit from volunteering. We demonstrate that the interaction between this information and one's private information makes it more likely that he or she will volunteer, given a higher level of contributions by his or her peers. We complement this theoretical work with an empirical analysis using Census 2000 Summary File 3 and Current Population Survey (CPS) 2004-2007 September supplement file data. We control for various individual and community characteristics, and employ robustness checks to verify the results of the baseline analysis. We additionally use an innovative instrumental variables strategy to account for reflection bias and endogeneity caused by selective sorting by individuals into neighborhoods, which allows us to argue for a causal interpretation. The empirical results in the baseline, as well as all robustness analyses, verify the main result of our theoretical model, and we employ a more general structure to further strengthen our results.

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In this analysis, we examine the relationship between an individual’s decision to volunteer and the average level of volunteering in the community where the individual resides. Our theoretical model is based on a coordination game , in which volunteering by others is informative regarding the benefit from volunteering. We demonstrate that the interaction between this information and one’s private information makes it more likely that he or she will volunteer, given a higher level of contributions by his or her peers. We complement this theoretical work with an empirical analysis using Census 2000 Summary File 3 and Current Population Survey (CPS) 2004-2007 September supplement file data. We control for various individual and community characteristics, and employ robustness checks to verify the results of the baseline analysis. We additionally use an innovative instrumental variables strategy to account for reflection bias and endogeneity caused by selective sorting by individuals into neighbourhoods, which allows us to argue for a causal interpretation. The empirical results in the baseline, as well as all robustness analyses, verify the main result of our theoretical model, and we employ a more general structure to further strengthen our results.