Assembling genes from predicted exons in linear time with dynamic programming

In a number of programs for gene structure prediction in higher eukaryotic genomic sequences, exon prediction is decoupled from gene assembly: a large pool of candidate exons is predicted and scored from features located in the query DNA sequence, and candidate genes are assembled from such a pool as sequences of nonoverlapping frame-compatible exons. Genes are scored as a function of the scores of the assembled exons, and the highest scoring candidate gene is assumed to be the most likely gene encoded by the query DNA sequence. Considering additive gene scoring functions, currently available algorithms to determine such a highest scoring candidate gene run in time proportional to the square of the number of predicted exons. Here, we present an algorithm whose running time grows only linearly with the size of the set of predicted exons. Polynomial algorithms rely on the fact that, while scanning the set of predicted exons, the highest scoring gene ending in a given exon can be obtained by appending the exon to the highest scoring among the highest scoring genes ending at each compatible preceding exon. The algorithm here relies on the simple fact that such highest scoring gene can be stored and updated. This requires scanning the set of predicted exons simultaneously by increasing acceptor and donor position. On the other hand, the algorithm described here does not assume an underlying gene structure model. Indeed, the definition of valid gene structures is externally defined in the so-called Gene Model. The Gene Model specifies simply which gene features are allowed immediately upstream which other gene features in valid gene structures. This allows for great flexibility in formulating the gene identification problem. In particular it allows for multiple-gene two-strand predictions and for considering gene features other than coding exons (such as promoter elements) in valid gene structures.

The Effect of occupational sex-composition on earnings: job-specialisation, sex-role attitudes and the division of domestic-labour in Spain

Important theoretical controversies remain unresolved in the literatire on occupational sex-segregation and the gender wage-gap. A useful way of summarising these controversies is viewing them as a debate between - cultural -socialisation. The paper discusses these theories in detail and carries out a preliminary test of the relative explanatory performance of some of their most consequential predictions. This is done by drawing on the Spanish sample of the second wave of the European Social Survey, ESS. The empirical analysis of ESS data illustrates the notable analytical pay-offs that can stem from using rich individual-level indicators, but also exemplifies the statistical llimitations generated by small sample size and high rates of non-response. Empirical results should, therefore, be taken as preliminary. They seem to suggest that the effect of occupational sex-segregation on wages could be explicable by workers' sex-role attitutes, their relative input in domestic production and the job-specific human capital requirements of their jobs. Of these three factors, job-specialisation seeems clearly the most important one.

Not the right job but a secure one : over-education and temporary employment in France, Italy and Spain

Resorting to four waves of the European Community Household Panel, this research explores the association between temporary employment and the likelihood of being over-educated. Such an association has been largely ignored by the literature explaining over-education, more inclined to attribute such a mismatch to the system of education. Selecting three similarly standarised and stratified systems of education (France, Italy and Spain) and controlling for many other variables likely to affect over-education, like gender, age, tenure, job change, firm size or sector, the paper demonstrates that such an association between temporary employment and over-education exists. Being a stepping stone towards a more stable and adjusted position in the labour market, holding a temporary employment may be associated to a higher likelihood of being over-educated. Such an association is more likely in Italy and France. Yet, the opposite sign prevails where permanent employment becomes such a valuable asset as to make individuals trade human capital by employment security. This is the case of Spain.

Finding a suitable job: the effect of the institutional context on self-perceived over-education

The current research compares the perception of over-education in four different European countries, resorting to European Household Panel Data. The results confirm that the type of educational system accounts for some of the cross-national differences in self-perceived over-education. In qualificational spaces, like Denmark, where vocational training receives more importance, self-perceived over-education is not associated as much with educational attainment as in the so-called’ organisational spaces’, like Spain, France and Italy. Yet, the results confirm that, controlling for the system of education, the traits and regulation of the labour market also have an effect on over-education. Thus, in Spain, where temporary employment has soared in recent decades, this type of contract is clearly associated with the perception of over-education, to a much higher extent than in Italy or France. Temporary contracts in Spain may not work as a steppig stone for attaining a job suitable to the training received by the individual, as they may in the case of France or Italy. In sum, not only institutions offering skills and human capital, but labour market regulation as well, have a clear impact on the incidence of over-education.

The influence of learning on evolution: a mathematical framework.

The Baldwin effect can be observed if phenotypic learning influences the evolutionary fitness of individuals, which can in turn accelerate or decelerate evolutionary change. Evidence for both learning-induced acceleration and deceleration can be found in the literature. Although the results for both outcomes were supported by specific mathematical or simulation models, no general predictions have been achieved so far. Here we propose a general framework to predict whether evolution benefits from learning or not. It is formulated in terms of the gain function, which quantifies the proportional change of fitness due to learning depending on the genotype value. With an inductive proof we show that a positive gain-function derivative implies that learning accelerates evolution, and a negative one implies deceleration under the condition that the population is distributed on a monotonic part of the fitness landscape. We show that the gain-function framework explains the results of several specific simulation models. We also use the gain-function framework to shed some light on the results of a recent biological experiment with fruit flies.

Executive Order Number Forty Seven, December 1982

Designate the Office of Planning and Programming as the Governors administrative agent for the Job Training Partnership ACT and the State Job Training Corrdinating Council.

Downsizing, Job Insecurity, and Firm Reputation

This paper studies how firms make layoff decisions in the presence of adverse shocks. In this uncertain environment, workers' expectations about their job security affect their on-the-job performance. This productivity effect on job insecurity forces firms to strike a balance between laying off redundant workers and maintaining survivors' commitment when deciding on the amount and timing of downsizing. This framework offers an explanation of conservative employment practices (such as zero or reduced layoffs) based on firms having private information about their future profits. High retention rates and wages can signal that the firm has a bright future, boosting workers' confidence. Moreover, the model provides clear predictions about when waves of downsizing will occur as opposed to one-time massive cuts.

Aitchison Geometry for Probability and Likelihood as a new approach to mathematical statistics

The Aitchison vector space structure for the simplex is generalized to a Hilbert space structure A2(P) for distributions and likelihoods on arbitrary spaces. Centralnotations of statistics, such as Information or Likelihood, can be identified in the algebraical structure of A2(P) and their corresponding notions in compositional data analysis, such as Aitchison distance or centered log ratio transform.In this way very elaborated aspects of mathematical statistics can be understoodeasily in the light of a simple vector space structure and of compositional data analysis. E.g. combination of statistical information such as Bayesian updating,combination of likelihood and robust M-estimation functions are simple additions/perturbations in A2(Pprior). Weighting observations corresponds to a weightedaddition of the corresponding evidence.Likelihood based statistics for general exponential families turns out to have aparticularly easy interpretation in terms of A2(P). Regular exponential families formfinite dimensional linear subspaces of A2(P) and they correspond to finite dimensionalsubspaces formed by their posterior in the dual information space A2(Pprior).The Aitchison norm can identified with mean Fisher information. The closing constant itself is identified with a generalization of the cummulant function and shown to be Kullback Leiblers directed information. Fisher information is the local geometry of the manifold induced by the A2(P) derivative of the Kullback Leibler information and the space A2(P) can therefore be seen as the tangential geometry of statistical inference at the distribution P.The discussion of A2(P) valued random variables, such as estimation functionsor likelihoods, give a further interpretation of Fisher information as the expected squared norm of evidence and a scale free understanding of unbiased reasoning

A mathematical excursion: From the three-door problem to a Cantor-type perfect set

We start with a generalization of the well-known three-door problem:the n-door problem. The solution of this new problem leads us toa beautiful representation system for real numbers in (0,1] as alternated series, known in the literature as Pierce expansions. A closer look to Pierce expansions will take us to some metrical properties of sets defined through the Pierce expansions of its elements. Finally, these metrical properties will enable us to present 'strange' sets, similar to the classical Cantor set.

Wage rigidity and job creation

Recent research in macroeconomics emphasizes the role of wage rigidity in accounting for the volatility of unemployment fluctuations. We use worker-level datafrom the CPS to measure the sensitivity of wages of newly hired workers to changesin aggregate labor market conditions. The wage of new hires, unlike the aggregatewage, is volatile and responds almost one-to-one to changes in labor productivity.We conclude that there is little evidence for wage stickiness in the data. We alsoshow, however, that a little wage rigidity goes a long way in amplifying the responseof job creation to productivity shocks.

Job satisfaction and life satisfaction: Analysis of a reciprocal model with social demographic moderators

The general objective of the study was to empirically test a reciprocal model of job satisfaction and life satisfaction while controlling for some social demographic variables. 827 employees working in 34 car dealerships in Northern Quebec (56% responses rate) were surveyed. The multiple item questionnaires were analysed using correlation analysis, chi square and ANOVAs. Results show interesting patterns emerging for the relationships between job and life satisfaction of which 49.2% of all individuals have spillover, 43.5% compensation, and 7.3% segmentation type of relationships. Results, nonetheless, are far richer and the model becomes much more refined when social demographic indicators are taken into account. Globally, social demographic variables demonstrate some effects on each satisfaction individually but also on the interrelation (nature of the relations) between life and work satisfaction.

A randomized concave programming method for choice network revenue management

Models incorporating more realistic models of customer behavior, as customers choosing froman offer set, have recently become popular in assortment optimization and revenue management.The dynamic program for these models is intractable and approximated by a deterministiclinear program called the CDLP which has an exponential number of columns. However, whenthe segment consideration sets overlap, the CDLP is difficult to solve. Column generationhas been proposed but finding an entering column has been shown to be NP-hard. In thispaper we propose a new approach called SDCP to solving CDLP based on segments and theirconsideration sets. SDCP is a relaxation of CDLP and hence forms a looser upper bound onthe dynamic program but coincides with CDLP for the case of non-overlapping segments. Ifthe number of elements in a consideration set for a segment is not very large (SDCP) can beapplied to any discrete-choice model of consumer behavior. We tighten the SDCP bound by(i) simulations, called the randomized concave programming (RCP) method, and (ii) by addingcuts to a recent compact formulation of the problem for a latent multinomial-choice model ofdemand (SBLP+). This latter approach turns out to be very effective, essentially obtainingCDLP value, and excellent revenue performance in simulations, even for overlapping segments.By formulating the problem as a separation problem, we give insight into why CDLP is easyfor the MNL with non-overlapping considerations sets and why generalizations of MNL posedifficulties. We perform numerical simulations to determine the revenue performance of all themethods on reference data sets in the literature.

A new compact linear programming formulation for choice network revenue management

The choice network revenue management model incorporates customer purchase behavioras a function of the offered products, and is the appropriate model for airline and hotel networkrevenue management, dynamic sales of bundles, and dynamic assortment optimization.The optimization problem is a stochastic dynamic program and is intractable. A certainty-equivalencerelaxation of the dynamic program, called the choice deterministic linear program(CDLP) is usually used to generate dyamic controls. Recently, a compact linear programmingformulation of this linear program was given for the multi-segment multinomial-logit (MNL)model of customer choice with non-overlapping consideration sets. Our objective is to obtaina tighter bound than this formulation while retaining the appealing properties of a compactlinear programming representation. To this end, it is natural to consider the affine relaxationof the dynamic program. We first show that the affine relaxation is NP-complete even for asingle-segment MNL model. Nevertheless, by analyzing the affine relaxation we derive a newcompact linear program that approximates the dynamic programming value function betterthan CDLP, provably between the CDLP value and the affine relaxation, and often comingclose to the latter in our numerical experiments. When the segment consideration sets overlap,we show that some strong equalities called product cuts developed for the CDLP remain validfor our new formulation. Finally we perform extensive numerical comparisons on the variousbounds to evaluate their performance.

Les quatre livres des rois : traduits en français du XIIe siècle. suivis d'un Fragment de moralités sur Job et d'un Choix de sermons de Saint Bernard / publiés par M. Le roux de Lincy,...

[Bible. A.T.. Samuel (ancien français). 1841]