Evolution of foraging behaviour in response to chronic malnutrition in Drosophila melanogaster.

Chronic exposure to food of low quality may exert conflicting selection pressures on foraging behaviour. On the one hand, more active search behaviour may allow the animal to find patches with slightly better, or more, food; on the other hand, such active foraging is energetically costly, and thus may be opposed by selection for energetic efficiency. Here, we test these alternative hypotheses in Drosophila larvae. We show that populations which experimentally evolved improved tolerance to larval chronic malnutrition have shorter foraging path length than unselected control populations. A behavioural polymorphism in foraging path length (the rover-sitter polymorphism) exists in nature and is attributed to the foraging locus (for). We show that a sitter strain (for(s2)) survives better on the poor food than the rover strain (for(R)), confirming that the sitter foraging strategy is advantageous under malnutrition. Larvae of the selected and control populations did not differ in global for expression. However, a quantitative complementation test suggests that the for locus may have contributed to the adaptation to poor food in one of the selected populations, either through a change in for allele frequencies, or by interacting epistatically with alleles at other loci. Irrespective of its genetic basis, our results provide two independent lines of evidence that sitter-like foraging behaviour is favoured under chronic larval malnutrition.

A test of Jessor's problem behavior theory in a Eurasian and a Western European developmental context.

PURPOSE: The current study tested the applicability of Jessor's problem behavior theory (PBT) in national probability samples from Georgia and Switzerland. Comparisons focused on (1) the applicability of the problem behavior syndrome (PBS) in both developmental contexts, and (2) on the applicability of employing a set of theory-driven risk and protective factors in the prediction of problem behaviors. METHODS: School-based questionnaire data were collected from n = 18,239 adolescents in Georgia (n = 9499) and Switzerland (n = 8740) following the same protocol. Participants rated five measures of problem behaviors (alcohol and drug use, problems because of alcohol and drug use, and deviance), three risk factors (future uncertainty, depression, and stress), and three protective factors (family, peer, and school attachment). Final study samples included n = 9043 Georgian youth (mean age = 15.57; 58.8% females) and n = 8348 Swiss youth (mean age = 17.95; 48.5% females). Data analyses were completed using structural equation modeling, path analyses, and post hoc z-tests for comparisons of regression coefficients. RESULTS: Findings indicated that the PBS replicated in both samples, and that theory-driven risk and protective factors accounted for 13% and 10% in Georgian and Swiss samples, respectively in the PBS, net the effects by demographic variables. Follow-up z-tests provided evidence of some differences in the magnitude, but not direction, in five of six individual paths by country. CONCLUSION: PBT and the PBS find empirical support in these Eurasian and Western European samples; thus, Jessor's theory holds value and promise in understanding the etiology of adolescent problem behaviors outside of the United States.

The impact of iron supplementation efficiency in female blood donors with a decreased ferritin level and no anaemia. Rationale and design of a randomised controlled trial: a study protocol.

ABSTRACT: BACKGROUND: There is no recommendation to screen ferritin level in blood donors, even though several studies have noted the high prevalence of iron deficiency after blood donation, particularly among menstruating females. Furthermore, some clinical trials have shown that non-anaemic women with unexplained fatigue may benefit from iron supplementation. Our objective is to determine the clinical effect of iron supplementation on fatigue in female blood donors without anaemia, but with a mean serum ferritin </= 30 ng/ml. METHODS/DESIGN: In a double blind randomised controlled trial, we will measure blood count and ferritin level of women under age 50 yr, who donate blood to the University Hospital of Lausanne Blood Transfusion Department, at the time of the donation and after 1 week. One hundred and forty donors with a ferritin level </= 30 ng/ml and haemoglobin level >/= 120 g/l (non-anaemic) a week after the donation will be included in the study and randomised. A one-month course of oral ferrous sulphate (80 mg/day of elemental iron) will be introduced vs. placebo. Self-reported fatigue will be measured using a visual analogue scale. Secondary outcomes are: score of fatigue (Fatigue Severity Scale), maximal aerobic power (Chester Step Test), quality of life (SF-12), and mood disorders (Prime-MD). Haemoglobin and ferritin concentration will be monitored before and after the intervention. DISCUSSION: Iron deficiency is a potential problem for all blood donors, especially menstruating women. To our knowledge, no other intervention study has yet evaluated the impact of iron supplementation on subjective symptoms after a blood donation. TRIAL REGISTRATION: NCT00689793.

Estimation of jump-diffusion processes via empirical characteristic functions

Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

Mynodbcsv: Lightweight Zero-Config Database Solution for Handling Very Large CSV Files.

Volumes of data used in science and industry are growing rapidly. When researchers face the challenge of analyzing them, their format is often the first obstacle. Lack of standardized ways of exploring different data layouts requires an effort each time to solve the problem from scratch. Possibility to access data in a rich, uniform manner, e.g. using Structured Query Language (SQL) would offer expressiveness and user-friendliness. Comma-separated values (CSV) are one of the most common data storage formats. Despite its simplicity, with growing file size handling it becomes non-trivial. Importing CSVs into existing databases is time-consuming and troublesome, or even impossible if its horizontal dimension reaches thousands of columns. Most databases are optimized for handling large number of rows rather than columns, therefore, performance for datasets with non-typical layouts is often unacceptable. Other challenges include schema creation, updates and repeated data imports. To address the above-mentioned problems, I present a system for accessing very large CSV-based datasets by means of SQL. It's characterized by: "no copy" approach - data stay mostly in the CSV files; "zero configuration" - no need to specify database schema; written in C++, with boost [1], SQLite [2] and Qt [3], doesn't require installation and has very small size; query rewriting, dynamic creation of indices for appropriate columns and static data retrieval directly from CSV files ensure efficient plan execution; effortless support for millions of columns; due to per-value typing, using mixed text/numbers data is easy; very simple network protocol provides efficient interface for MATLAB and reduces implementation time for other languages. The software is available as freeware along with educational videos on its website [4]. It doesn't need any prerequisites to run, as all of the libraries are included in the distribution package. I test it against existing database solutions using a battery of benchmarks and discuss the results.

Pharmacokinetic (PK)-based dosage individualization of imatinib: evaluation of efficiency and clinical usefulness

Background: Retrospective analyses suggest that personalized PK-based dosage might be useful for imatinib, as treatment response correlates with trough concentrations (Cmin) in cancer patients. Our objectives were to improve the interpretation of randomly measured concentrations and to confirm its efficiency before evaluating the clinical usefulness of systematic PK-based dosage in chronic myeloid leukemia patients. Methods and Results: A Bayesian method was validated for the prediction of individual Cmin on the basis of a single random observation, and was applied in a prospective multicenter randomized controlled clinical trial. 28 out of 56 patients were enrolled in the systematic dosage individualization arm and had 44 follow-up visits (their clinical follow-up is ongoing). PK-dose-adjustments were proposed in 39% having predicted Cmin significantly away from the target (1000 ng/ml). Recommendations were taken up by physicians in 57%, patients were considered non-compliant in 27%. Median Cmin at study inclusion was 754 ng/ml and differed significantly from the target (p=0.02, Wilcoxon test). On follow-up, Cmin was 984 ng/ml (p=0.82) in the compliant group. CV decreased from 46% to 27% (p=0.02, F-test). Conclusion: PK-based (Bayesian) dosage adjustment is able to bring individual drug exposure closer to a given therapeutic target. Its influence on therapeutic response remains to be evaluated.

Test methods: anabolics.

In the International Olympic Committee (IOC) accredited laboratories, specific methods have been developed to detect anabolic steroids in athletes' urine. The technique of choice to achieve this is gas-chromatography coupled with mass spectrometry (GC-MS). In order to improve the efficiency of anti-doping programmes, the laboratories have defined new analytical strategies. The final sensitivity of the analytical procedure can be improved by choosing new technologies for use in detection, such as tandem mass spectrometry (MS-MS) or high resolution mass spectrometry (HRMS). A better sample preparation using immuno-affinity chromatography (IAC) is also a good tool for improving sensitivity. These techniques are suitable for the detection of synthetic anabolic steroids whose structure is not found naturally in the human body. The more and more evident use, on a large scale, of substances chemically similar to the endogenous steroids obliges both the laboratory and the sports authorities to use the steroid profile of the athlete in comparison with reference ranges from a population or with intraindividual reference values.

Explaining Fiscal Balances with a Simultaneous Equation Model of Revenue and Expenditure : A Case Study of Swiss Cantons Using Panel Data

Empirical literature on the analysis of the efficiency of measures for reducing persistent government deficits has mainly focused on the direct explanation of deficit. By contrast, this paper aims at modeling government revenue and expenditure within a simultaneous framework and deriving the fiscal balance (surplus or deficit) equation as the difference between the two variables. This setting enables one to not only judge how relevant the explanatory variables are in explaining the fiscal balance but also understand their impact on revenue and/or expenditure. Our empirical results, obtained by using a panel data set on Swiss Cantons for the period 1980-2002, confirm the relevance of the approach followed here, by providing unambiguous evidence of a simultaneous relationship between revenue and expenditure. They also reveal strong dynamic components in revenue, expenditure, and fiscal balance. Among the significant determinants of public fiscal balance we not only find the usual business cycle elements, but also and more importantly institutional factors such as the number of administrative units, and the ease with which people can resort to political (direct democracy) instruments, such as public initiatives and referendum.

Determinants of school efficiency : The case of primary schools in the State of Geneva, Switzerland

The public primary school system in the State of Geneva, Switzerland, is characterized by centrally evaluated pupil performance measured with the use of standardized tests. As a result, consistent data are collected among the system. The 2010-2011 dataset is used to develop a two-stage data envelopment analysis (DEA) of school efficiency. In the first stage, DEA is employed to calculate an individual efficiency score for each school. It shows that, on average, each school could reduce its inputs by 7% whilst maintaining the same quality of pupil performance. The cause of inefficiency lies in perfectible management. In the second stage, efficiency is regressed on school characteristics and environmental variables;external factors outside of the control of headteachers. The model is tested for multicollinearity, heteroskedasticity and endogeneity. Four variables are identified as statistically significant. School efficiency is negatively influenced by (1) the provision of special education, (2) the proportion of disadvantaged pupils enrolled at the school and (3) operations being held on multiple sites, but positively influenced by school size (captured by the number of pupils). The proportion of allophone pupils; schools located in urban areas and the provision of reception classes for immigrant pupils are not significant. Although the significant variables influencing school efficiency are outside of the control of headteachers, it is still possible to either boost the positive impact or curb the negative impact. Dans le canton de Genève (Suisse), les écoles publiques primaires sont caractérisées par un financement assuré par les collectivités publiques (canton et communes) et par une évaluation des élèves à l'aide d'épreuves standardisées à trois moments distincts de leur scolarité. Cela permet de réunir des informations statistiques consistantes. La base de données de l'année 2010-2011 est utilisée dans une analyse en deux étapes de l'efficience des écoles. Dans une première étape, la méthode d'analyse des données par enveloppement (DEA) est utilisée pour calculer un score d'efficience pour chaque école. Cette analyse démontre que l'efficience moyenne des écoles s'élève à 93%. Chaque école pourrait, en moyenne, réduire ses ressources de 7% tout en conservant constants les résultats des élèves aux épreuves standardisées. La source de l'inefficience réside dans un management des écoles perfectible. Dans une seconde étape, les scores d'efficience sont régressés sur les caractéristiques des écoles et sur des variables environnementales. Ces variables ne sont pas sous le contrôle (ou l'influence) des directeurs d'école. Le modèle est testé pour la multicolinéartié, l'hétéroscédasticité et l'endogénéité. Quatre variables sont statistiquement significatives. L'efficience des écoles est influencée négativement par (1) le fait d'offrir un enseignement spécialisé en classe séparée, (2) la proporition d'élèves défavorisés et (3) le fait d'opérer sur plusieurs sites différents. L'efficience des écoles est influencée positivement par la taille de l'école, mesurée par le nombre d'élèves. La proporition d'élèves allophones, le fait d'être situé dans une zone urbaine et d'offrir des classes d'accueil pour les élèves immigrants constituent autant de variables non significatives. Le fait que les variables qui influencent l'efficience des écoles ne soient pas sous le contrôle des directeurs ne signifie pas qu'il faille céder au fatalisme. Différentes pistes sont proposées pour permettre soit de réduire l'impact négatif soit de tirer parti de l'impact positif des variables significatives.

Efficiency of Gumbel analyses for determining extreme daily precipitation in Switzerland

Gumbel analyses were carried out on rainfall time-series at 151 locations in Switzerland for 4 different periods of 30 years in order to estimate daily extreme precipitation for a return period of 100 years. Those estimations were compared with maximal daily values measured during the last 100 years (1911-2010) to test the efficiency of these analyses. This comparison shows that these analyses provide good results for 50 to 60% locations in this country from rainfall time-series 1961-1990 and 1980-2010. On the other hand, daily precipitation with a return period of 100 years is underestimated at most locations from time-series 1931-1960 and especially 1911-1940. Such underestimation results from the increase of maximal daily precipitation recorded from 1911 to 2010 at 90% locations in Switzerland.

Swain: Stata module to correct the SEM chi-square overidentification test in small sample sizes or complex models. Statistical Software Components S457617, Boston College Department of Economics.

Swain corrects the chi-square overidentification test (i.e., likelihood ratio test of fit) for structural equation models whethr with or without latent variables. The chi-square statistic is asymptotically correct; however, it does not behave as expected in small samples and/or when the model is complex (cf. Herzog, Boomsma, & Reinecke, 2007). Thus, particularly in situations where the ratio of sample size (n) to the number of parameters estimated (p) is relatively small (i.e., the p to n ratio is large), the chi-square test will tend to overreject correctly specified models. To obtain a closer approximation to the distribution of the chi-square statistic, Swain (1975) developed a correction; this scaling factor, which converges to 1 asymptotically, is multiplied with the chi-square statistic. The correction better approximates the chi-square distribution resulting in more appropriate Type 1 reject error rates (see Herzog & Boomsma, 2009; Herzog, et al., 2007).

Financial Markets and Real Ecinomy: Four Essays in International Trade

Financial markets play an important role in an economy performing various functions like mobilizing and pooling savings, producing information about investment opportunities, screening and monitoring investments, implementation of corporate governance, diversification and management of risk. These functions influence saving rates, investment decisions, technological innovation and, therefore, have important implications for welfare. In my PhD dissertation I examine the interplay of financial and product markets by looking at different channels through which financial markets may influence an economy.My dissertation consists of four chapters. The first chapter is a co-authored work with Martin Strieborny, a PhD student from the University of Lausanne. The second chapter is a co-authored work with Melise Jaud, a PhD student from the Paris School of Economics. The third chapter is co-authored with both Melise Jaud and Martin Strieborny. The last chapter of my PhD dissertation is a single author paper.Chapter 1 of my PhD thesis analyzes the effect of financial development on growth of contract intensive industries. These industries intensively use intermediate inputs that neither can be sold on organized exchange, nor are reference-priced (Levchenko, 2007; Nunn, 2007). A typical example of a contract intensive industry would be an industry where an upstream supplier has to make investments in order to customize a product for needs of a downstream buyer. After the investment is made and the product is adjusted, the buyer may refuse to meet a commitment and trigger ex post renegotiation. Since the product is customized to the buyer's needs, the supplier cannot sell the product to a different buyer at the original price. This is referred in the literature as the holdup problem. As a consequence, the individually rational suppliers will underinvest into relationship-specific assets, hurting the downstream firms with negative consequences for aggregate growth. The standard way to mitigate the hold up problem is to write a binding contract and to rely on the legal enforcement by the state. However, even the most effective contract enforcement might fail to protect the supplier in tough times when the buyer lacks a reliable source of external financing. This suggests the potential role of financial intermediaries, banks in particular, in mitigating the incomplete contract problem. First, financial products like letters of credit and letters of guarantee can substantially decrease a risk and transaction costs of parties. Second, a bank loan can serve as a signal about a buyer's true financial situation, an upstream firm will be more willing undertake relationship-specific investment knowing that the business partner is creditworthy and will abstain from myopic behavior (Fama, 1985; von Thadden, 1995). Therefore, a well-developed financial (especially banking) system should disproportionately benefit contract intensive industries.The empirical test confirms this hypothesis. Indeed, contract intensive industries seem to grow faster in countries with a well developed financial system. Furthermore, this effect comes from a more developed banking sector rather than from a deeper stock market. These results are reaffirmed examining the effect of US bank deregulation on the growth of contract intensive industries in different states. Beyond an overall pro-growth effect, the bank deregulation seems to disproportionately benefit the industries requiring relationship-specific investments from their suppliers.Chapter 2 of my PhD focuses on the role of the financial sector in promoting exports of developing countries. In particular, it investigates how credit constraints affect the ability of firms operating in agri-food sectors of developing countries to keep exporting to foreign markets.Trade in high-value agri-food products from developing countries has expanded enormously over the last two decades offering opportunities for development. However, trade in agri-food is governed by a growing array of standards. Sanitary and Phytosanitary standards (SPS) and technical regulations impose additional sunk, fixed and operating costs along the firms' export life. Such costs may be detrimental to firms' survival, "pricing out" producers that cannot comply. The existence of these costs suggests a potential role of credit constraints in shaping the duration of trade relationships on foreign markets. A well-developed financial system provides the funds to exporters necessary to adjust production processes in order to meet quality and quantity requirements in foreign markets and to maintain long-standing trade relationships. The products with higher needs for financing should benefit the most from a well functioning financial system. This differential effect calls for a difference-in-difference approach initially proposed by Rajan and Zingales (1998). As a proxy for demand for financing of agri-food products, the sanitary risk index developed by Jaud et al. (2009) is used. The empirical literature on standards and norms show high costs of compliance, both variable and fixed, for high-value food products (Garcia-Martinez and Poole, 2004; Maskus et al., 2005). The sanitary risk index reflects the propensity of products to fail health and safety controls on the European Union (EU) market. Given the high costs of compliance, the sanitary risk index captures the demand for external financing to comply with such regulations.The prediction is empirically tested examining the export survival of different agri-food products from firms operating in Ghana, Mali, Malawi, Senegal and Tanzania. The results suggest that agri-food products that require more financing to keep up with food safety regulation of the destination market, indeed sustain longer in foreign market, when they are exported from countries with better developed financial markets.Chapter 3 analyzes the link between financial markets and efficiency of resource allocation in an economy. Producing and exporting products inconsistent with a country's factor endowments constitutes a serious misallocation of funds, which undermines competitiveness of the economy and inhibits its long term growth. In this chapter, inefficient exporting patterns are analyzed through the lens of the agency theories from the corporate finance literature. Managers may pursue projects with negative net present values because their perquisites or even their job might depend on them. Exporting activities are particularly prone to this problem. Business related to foreign markets involves both high levels of additional spending and strong incentives for managers to overinvest. Rational managers might have incentives to push for exports that use country's scarce factors which is suboptimal from a social point of view. Export subsidies might further skew the incentives towards inefficient exporting. Management can divert the export subsidies into investments promoting inefficient exporting.Corporate finance literature stresses the disciplining role of outside debt in counteracting the internal pressures to divert such "free cash flow" into unprofitable investments. Managers can lose both their reputation and the control of "their" firm if the unpaid external debt triggers a bankruptcy procedure. The threat of possible failure to satisfy debt service payments pushes the managers toward an efficient use of available resources (Jensen, 1986; Stulz, 1990; Hart and Moore, 1995). The main sources of debt financing in the most countries are banks. The disciplining role of banks might be especially important in the countries suffering from insufficient judicial quality. Banks, in pursuing their rights, rely on comparatively simple legal interventions that can be implemented even by mediocre courts. In addition to their disciplining role, banks can promote efficient exporting patterns in a more direct way by relaxing credit constraints of producers, through screening, identifying and investing in the most profitable investment projects. Therefore, a well-developed domestic financial system, and particular banking system, would help to push a country's exports towards products congruent with its comparative advantage.This prediction is tested looking at the survival of different product categories exported to US market. Products are identified according to the Euclidian distance between their revealed factor intensity and the country's factor endowments. The results suggest that products suffering from a comparative disadvantage (labour-intensive products from capital-abundant countries) survive less on the competitive US market. This pattern is stronger if the exporting country has a well-developed banking system. Thus, a strong banking sector promotes exports consistent with a country comparative advantage.Chapter 4 of my PhD thesis further examines the role of financial markets in fostering efficient resource allocation in an economy. In particular, the allocative efficiency hypothesis is investigated in the context of equity market liberalization.Many empirical studies document a positive and significant effect of financial liberalization on growth (Levchenko et al. 2009; Quinn and Toyoda 2009; Bekaert et al., 2005). However, the decrease in the cost of capital and the associated growth in investment appears rather modest in comparison to the large GDP growth effect (Bekaert and Harvey, 2005; Henry, 2000, 2003). Therefore, financial liberalization may have a positive impact on growth through its effect on the allocation of funds across firms and sectors.Free access to international capital markets allows the largest and most profitable domestic firms to borrow funds in foreign markets (Rajan and Zingales, 2003). As domestic banks loose some of their best clients, they reoptimize their lending practices seeking new clients among small and younger industrial firms. These firms are likely to be more risky than large and established companies. Screening of customers becomes prevalent as the return to screening rises. Banks, ceteris paribus, tend to focus on firms operating in comparative-advantage sectors because they are better risks. Firms in comparative-disadvantage sectors finding it harder to finance their entry into or survival in export markets either exit or refrain from entering export markets. On aggregate, one should therefore expect to see less entry, more exit, and shorter survival on export markets in those sectors after financial liberalization.The paper investigates the effect of financial liberalization on a country's export pattern by comparing the dynamics of entry and exit of different products in a country export portfolio before and after financial liberalization.The results suggest that products that lie far from the country's comparative advantage set tend to disappear relatively faster from the country's export portfolio following the liberalization of financial markets. In other words, financial liberalization tends to rebalance the composition of a country's export portfolio towards the products that intensively use the economy's abundant factors.

Differential DNA extraction of challenging simulated sexual assault samples: a Swiss collaborative study.

ABSTRACT: In sexual assault cases, autosomal DNA analysis of gynecological swabs is a challenge, as the presence of a large quantity of female material may prevent the detection of the male DNA. A solution to this problem is differential DNA extraction, but as there are different protocols, it was decided to test their efficiency on simulated casework samples. Four difficult samples were sent to the nine Swiss laboratories active in the forensic genetics. They used their routine protocols to separate the epithelial cell fraction, enriched with the non-sperm DNA, from the sperm fraction. DNA extracts were then sent to the organizing laboratory for analysis. Estimates of male to female DNA ratio without differential DNA extraction ranged from 1:38 to 1:339, depending on the semen used to prepare the samples. After differential DNA extraction, most of the ratios ranged from 1:12 to 9:1, allowing the detection of the male DNA. Compared to direct DNA extraction, cell separation resulted in losses of 94-98% of the male DNA. As expected, more male DNA was generally present in the sperm than in the epithelial cell fraction. However, for about 30% of the samples, the reverse trend was observed. The recovery of male and female DNA was highly variable depending on the laboratories. Experimental design similar to the one used in this study may help for local protocol testing and improvement.