Probe-specific mixed-model approach to detect copy number differences using multiplex ligation-dependent probe amplification (MLPA)

Background: MLPA method is a potentially useful semi-quantitative method to detect copy number alterations in targeted regions. In this paper, we propose a method for the normalization procedure based on a non-linear mixed-model, as well as a new approach for determining the statistical significance of altered probes based on linear mixed-model. This method establishes a threshold by using different tolerance intervals that accommodates the specific random error variability observed in each test sample.Results: Through simulation studies we have shown that our proposed method outperforms two existing methods that are based on simple threshold rules or iterative regression. We have illustrated the method using a controlled MLPA assay in which targeted regions are variable in copy number in individuals suffering from different disorders such as Prader-Willi, DiGeorge or Autism showing the best performace.Conclusion: Using the proposed mixed-model, we are able to determine thresholds to decide whether a region is altered. These threholds are specific for each individual, incorporating experimental variability, resulting in improved sensitivity and specificity as the examples with real data have revealed.

Ground and excited states of KNiF3: An ab initio cluster-model approach

Finite cluster models and a variety of ab initio wave functions have been used to study the electronic structure of bulk KNiF3. Several electronic states, including the ground state and some charge-transfer excited states, have been considered. The study of the cluster-model wave functions has permitted an understanding of the nature of the chemical bond in the electronic ground state. This is found to be highly ionic and the different ionic and covalent contributions to the bonding have been identified and quantified. Finally, we have studied the charge-transfer excited states leading to the optical gap and have found that calculated and experimental values are in good agreement. The wave functions corresponding to these excited states have also been analyzed and show that although KNiF3 may be described as a ligand-to-metal charge-transfer insulator there is a strong configuration mixing with the metal-to-metal charge-transfer states.

Response of fine root respiration to variations in biotic and abiotic factors in a mixed Mediterranean forest affected by drought-induced secondary succession

Understanding the factors controlling fine root respiration (FRR) at different temporal scales will help to improve our knowledge about the spatial and temporal variability of soil respiration (SR) and to improve future predictions of CO2 effluxes to the atmosphere. Here we present a comparative study of how FRR respond to variability in soil temperature and moisture in two widely spread species, Scots pines (Pinus sylvestris L.) and Holm-oaks (HO; Quercus ilex L.). Those two species show contrasting water use strategies during the extreme summer-drought conditions that characterize the Mediterranean climate. The study was carried out on a mixed Mediterranean forest where Scots pines affected by drought induced die-back are slowly being replaced by the more drought resistant HO. FRR was measured in spring and early fall 2013 in excised roots freshly removed from the soil and collected under HO and under Scots pines at three different health stages: dead (D), defoliated (DP) and non-defoliated (NDP). Variations in soil temperature, soil water content and daily mean assimilation per tree were also recorded to evaluate FRR sensibility to abiotic and biotic environmental variations. Our results show that values of FRR were substantially lower under HO (1.26 ± 0.16 microgram CO2 /groot·min) than under living pines (1.89 ± 0.19 microgram CO2 /groot·min) which disagrees with the similar rates of soil respiration previously observed under both canopies and suggest that FRR contribution to total SR varies under different tree species. The similarity of FRR rates under HO and DP furthermore confirms other previous studies suggesting a recent Holm-oak root colonization of the gaps under dead trees. A linear mixed effect model approach indicated that seasonal variations in FRR were best explained by soil temperature (p<0.05) while soil moisture was not exerting any direct control over FRR, despite the low soil moisture values during the summer sampling. Plant assimilation rates were positively related to FRR explaining part of the observed variability (p<0.01). However the positive relations of FRR with plant assimilation occurred mainly during spring, when both soil moisture and plant assimilation rates were higher. Our results finally suggest that plants might be able to maintain relatively high rates of FRR during the sub-optimal abiotic and biotic summer conditions probably thanks to their capacity to re-mobilize carbon reserves and their capacity to passively move water from moister layers to upper layers with lower water potentials (where the FR were collected) by hydraulic lift.

A correlation sensitivity analysis of non-life underwriting risk in solvency capital requirement estimation

This paper analyses the impact of using different correlation assumptions between lines of business when estimating the risk-based capital reserve, the Solvency Capital Requirement (SCR), under Solvency II regulations. A case study is presented and the SCR is calculated according to the Standard Model approach. Alternatively, the requirement is then calculated using an Internal Model based on a Monte Carlo simulation of the net underwriting result at a one-year horizon, with copulas being used to model the dependence between lines of business. To address the impact of these model assumptions on the SCR we conduct a sensitivity analysis. We examine changes in the correlation matrix between lines of business and address the choice of copulas. Drawing on aggregate historical data from the Spanish non-life insurance market between 2000 and 2009, we conclude that modifications of the correlation and dependence assumptions have a significant impact on SCR estimation.

Life-Cycle Effects on Household Expenditures: A Latent-Variable Approach

Using data from the Spanish household budget survey, we investigate life- cycle effects on several product expenditures. A latent-variable model approach is adopted to evaluate the impact of income on expenditures, controlling for the number of members in the family. Two latent factors underlying repeated measures of monetary and non-monetary income are used as explanatory variables in the expenditure regression equations, thus avoiding possible bias associated to the measurement error in income. The proposed methodology also takes care of the case in which product expenditures exhibit a pattern of infrequent purchases. Multiple-group analysis is used to assess the variation of key parameters of the model across various household life-cycle typologies. The analysis discloses significant life-cycle effects on the mean levels of expenditures; it also detects significant life-cycle effects on the way expenditures are affected by income and family size. Asymptotic robust methods are used to account for possible non-normality of the data.

Lyfe-cycle effects on household expenditures: A latent-variable approach

Using data from the Spanish household budget survey, we investigate life-cycle effects on several product expenditures. A latent-variable model approach is adopted to evaluate the impact of income on expenditures, controlling for the number of members in the family. Two latent factors underlying repeated measures of monetary and non-monetary income are used as explanatory variables in the expenditure regression equations, thus avoiding possible bias associated to the measurement error in income. The proposed methodology also takes care of the case in which product expenditures exhibit a pattern of infrequent purchases. Multiple-group analysis is used to assess the variation of key parameters of the model across various household life-cycle typologies. The analysis discloses significant life-cycle effects on the mean levels of expenditures; it also detects significant life-cycle effects on the way expenditures are affected by income and family size. Asymptotic robust methods are used to account for possible non-normality of the data.

System identification using a linear combination of cumulant slices

In this paper we develop a new linear approach to identify the parameters of a moving average (MA) model from the statistics of the output. First, we show that, under some constraints, the impulse response of the system can be expressed as a linear combination of cumulant slices. Then, thisresult is used to obtain a new well-conditioned linear methodto estimate the MA parameters of a non-Gaussian process. Theproposed method presents several important differences withexisting linear approaches. The linear combination of slices usedto compute the MA parameters can be constructed from dif-ferent sets of cumulants of different orders, providing a generalframework where all the statistics can be combined. Further-more, it is not necessary to use second-order statistics (the autocorrelation slice), and therefore the proposed algorithm stillprovides consistent estimates in the presence of colored Gaussian noise. Another advantage of the method is that while mostlinear methods developed so far give totally erroneous estimates if the order is overestimated, the proposed approach doesnot require a previous estimation of the filter order. The simulation results confirm the good numerical conditioning of thealgorithm and the improvement in performance with respect to existing methods.

A correlation sensitivity analysis of non-life underwriting risk in solvency capital requirement estimation

This paper analyses the impact of using different correlation assumptions between lines of business when estimating the risk-based capital reserve, the Solvency Capital Requirement -SCR-, under Solvency II regulations. A case study is presented and the SCR is calculated according to the Standard Model approach. Alternatively, the requirement is then calculated using an Internal Model based on a Monte Carlo simulation of the net underwriting result at a one-year horizon, with copulas being used to model the dependence between lines of business. To address the impact of these model assumptions on the SCR we conduct a sensitivity analysis. We examine changes in the correlation matrix between lines of business and address the choice of copulas. Drawing on aggregate historical data from the Spanish non-life insurance market between 2000 and 2009, we conclude that modifications of the correlation and dependence assumptions have a significant impact on SCR estimation.

Tax reforms and inequality: theoretical and empirical implications

In this paper we examine the effect of tax policy on the relationship between inequality and growth in a two-sector non-scale model. With non-scale models, the longrun equilibrium growth rate is determined by technological parameters and it is independent of macroeconomic policy instruments. However, this fact does not imply that fiscal policy is unimportant for long-run economic performance. It indeed has important effects on the different levels of key economic variables such as per capita stock of capital and output. Hence, although the economy grows at the same rate across steady states, the bases for economic growth may be different.The model has three essential features. First, we explicitly model skill accumulation, second, we introduce government finance into the production function, and we introduce an income tax to mirror the fiscal events of the 1980¿s and 1990¿s in the US. The fact that the non-scale model is associated with higher order dynamics enables it to replicate the distinctly non-linear nature of inequality in the US with relative ease. The results derived in this paper attract attention to the fact that the non-scale growth model does not only fit the US data well for the long-run (Jones, 1995b) but also that it possesses unique abilities in explaining short term fluctuations of the economy. It is shown that during transition the response of the relative simulated wage to changes in the tax code is rather non-monotonic, quite in accordance to the US inequality pattern in the 1980¿s and early 1990¿s.More specifically, we have analyzed in detail the dynamics following the simulation of an isolated tax decrease and an isolated tax increase. So, after a tax decrease the skill premium follows a lower trajectory than the one it would follow without a tax decrease. Hence we are able to reduce inequality for several periods after the fiscal shock. On the contrary, following a tax increase, the evolution of the skill premium remains above the trajectory carried on by the skill premium under a situation with no tax increase. Consequently, a tax increase would imply a higher level of inequality in the economy

Tax reforms and inequality: theoretical and empirical implications

In this paper we examine the effect of tax policy on the relationship between inequality and growth in a two-sector non-scale model. With non-scale models, the longrun equilibrium growth rate is determined by technological parameters and it is independent of macroeconomic policy instruments. However, this fact does not imply that fiscal policy is unimportant for long-run economic performance. It indeed has important effects on the different levels of key economic variables such as per capita stock of capital and output. Hence, although the economy grows at the same rate across steady states, the bases for economic growth may be different.The model has three essential features. First, we explicitly model skill accumulation, second, we introduce government finance into the production function, and we introduce an income tax to mirror the fiscal events of the 1980¿s and 1990¿s in the US. The fact that the non-scale model is associated with higher order dynamics enables it to replicate the distinctly non-linear nature of inequality in the US with relative ease. The results derived in this paper attract attention to the fact that the non-scale growth model does not only fit the US data well for the long-run (Jones, 1995b) but also that it possesses unique abilities in explaining short term fluctuations of the economy. It is shown that during transition the response of the relative simulated wage to changes in the tax code is rather non-monotonic, quite in accordance to the US inequality pattern in the 1980¿s and early 1990¿s.More specifically, we have analyzed in detail the dynamics following the simulation of an isolated tax decrease and an isolated tax increase. So, after a tax decrease the skill premium follows a lower trajectory than the one it would follow without a tax decrease. Hence we are able to reduce inequality for several periods after the fiscal shock. On the contrary, following a tax increase, the evolution of the skill premium remains above the trajectory carried on by the skill premium under a situation with no tax increase. Consequently, a tax increase would imply a higher level of inequality in the economy

Obesity and the incidence of chronic diseases: a seemingly unrelated probit approach

Western societies can reduce avoidable mortality and morbidity by better understanding the relationship between obesity and chronic disease. This paper examines the joint determinants of obesity and of heart disease, diabetes, hypertension, and elevated cholesterol. It analyzes a broadly representative Spanish dataset, the 1999 Survey on Disabilities, Impairments and Health Status, using a health production theoretical framework together with a seemingly unrelated probit model approach that controls for unobserved heterogeneity and endogeneity. Its findings provide suggestive evidence of a positive and significant, although specification-dependent, association between obesity and the prevalence of chronic illness

Obesity and the incidence of chronic diseases: a seemingly unrelated probit approach

Western societies can reduce avoidable mortality and morbidity by better understanding the relationship between obesity and chronic disease. This paper examines the joint determinants of obesity and of heart disease, diabetes, hypertension, and elevated cholesterol. It analyzes a broadly representative Spanish dataset, the 1999 Survey on Disabilities, Impairments and Health Status, using a health production theoretical framework together with a seemingly unrelated probit model approach that controls for unobserved heterogeneity and endogeneity. Its findings provide suggestive evidence of a positive and significant, although specification-dependent, association between obesity and the prevalence of chronic illness

Impact of Duration of Primary Education on School Enrollment, Graduation and Drop-outs: A Cross- Country Analysis

Using a panel data for non-OECD countries covering the period 1970-2012, this chapter analyzes the impact of the duration of primary education on school enrollment, drop-out and completion rates. The empirical results show that for children in elementary school one ad- ditional grade of primary education have a negative impact on the enrollment rate, while the e ect on drop-outs is positive. Analogously, it is obtained that an additional grade in primary education reduces the enrollment rate in secondary education. These results are in line with the fertility model approach, that is, in developing and underdeveloped countries parents do not have incentive to send children to school given the high perceived economic value of children.

Technical Note: Dissolved organic matter fluorescence a finite mixture approach to deconvolve excitation-emission matrices

The analysis of the shape of excitation-emission matrices (EEMs) is a relevant tool for exploring the origin, transport and fate of dissolved organic matter (DOM) in aquatic ecosystems. Within this context, the decomposition of EEMs is acquiring a notable relevance. A simple mathematical algorithm that automatically deconvolves individual EEMs is described, creating new possibilities for the comparison of DOM fluorescence properties and EEMs that are very different from each other. A mixture model approach is adopted to decompose complex surfaces into sub-peaks. The laplacian operator and the Nelder-Mead optimisation algorithm are implemented to individuate and automatically locate potential peaks in the EEM landscape. The EEMs of a simple artificial mixture of fluorophores and DOM samples collected in a Mediterranean river are used to describe the model application and to illustrate a strategy that optimises the search for the optimal output.

Firm Size and Geographical Aggregation: An Empirical Appraisal in Industrial Location

This paper assesses empirically the importance of size discrimination and disaggregate data for deciding where to locate a start-up concern. We compare three econometric specifications using Catalan data: a multinomial logit with 4 and 41 alternatives (provinces and comarques, respectively) in which firm size is the main covariate; a conditional logit with 4 and 41 alternatives including attributes of the sites as well as size-site interactions; and a Poisson model on the comarques and the full spatial choice set (942 municipalities) with site-specific variables. Our results suggest that if these two issues are ignored, conclusions may be misleading. We provide evidence that large and small firms behave differently and conclude that Catalan firms tend to choose between comarques rather than between municipalities. Moreover, labour-intensive firms seem more likely to be located in the city of Barcelona. Keywords: Catalonia, industrial location, multinomial response model. JEL: C250, E30, R00, R12