Merging the hypothetical extraction method and the classical multiplier approach: a hybrid possibility for identifying key distributive sectors

The two main alternative methods used to identify key sectors within the input-output approach, the Classical Multiplier method (CMM) and the Hypothetical Extraction method (HEM), are formally and empirically compared in this paper. Our findings indicate that the main distinction between the two approaches stems from the role of the internal effects. These internal effects are quantified under the CMM while under the HEM only external impacts are considered. In our comparison, we find, however that CMM backward measures are more influenced by within-block effects than the proposed forward indices under this approach. The conclusions of this comparison allow us to develop a hybrid proposal that combines these two existing approaches. This hybrid model has the advantage of making it possible to distinguish and disaggregate external effects from those that a purely internal. This proposal has also an additional interest in terms of policy implications. Indeed, the hybrid approach may provide useful information for the design of ''second best'' stimulus policies that aim at a more balanced perspective between overall economy-wide impacts and their sectoral distribution.

Identifying protein-coding genes in genomic sequences

The vast majority of the biology of a newly sequenced genome is inferred from the set of encoded proteins. Predicting this set is therefore invariably the first step after the completion of the genome DNA sequence. Here we review the main computational pipelines used to generate the human reference protein-coding gene sets.

Identifying monetary policy shocks in Japan

It is sometimes argued that the central banks influence the private economy in the short run through controlling a specific component of high powered money, not its total amount. Using a structural VAR approach, this paper evaluates this claim empirically, in the context of the Japanese economy. I estimate a model based on the standard view that the central bank controls the total amount of high powered money, and another model based on the alternative view that it controls only a specific component. It is shown that the former yields much more sensible estimates than thelatter.

Identifying the socioeconomic determinants of crime in Spanish provinces

In this paper we study, having as theoretical reference the economic model of crime (Becker, 1968; Ehrlich, 1973), which are the socioeconomic and demographic determinants of crime in Spain paying attention on the role of provincial peculiarities. We estimate a crime equation using a panel dataset of Spanish provinces (NUTS3) for the period 1993 to 1999 employing the GMMsystem estimator. Empirical results suggest that lagged crime rate and clear-up rate are correlated to all typologies of crime rate considered. Property crimes are better explained by socioeconomic variables (GDP per capita, GDP growth rate and percentage of population with high school and university degree), while demographic factors reveal important and significant influences, in particular for crimes against the person. These results are obtained using an instrumental variable approach that takes advantage of the dynamic properties of our dataset to control for both measurement errors in crime data and joint endogeneity of the explanatory variables

Identifying the socioeconomic determinants of crime in Spanish provinces

In this paper we study, having as theoretical reference the economic model of crime (Becker, 1968; Ehrlich, 1973), which are the socioeconomic and demographic determinants of crime in Spain paying attention on the role of provincial peculiarities. We estimate a crime equation using a panel dataset of Spanish provinces (NUTS3) for the period 1993 to 1999 employing the GMMsystem estimator. Empirical results suggest that lagged crime rate and clear-up rate are correlated to all typologies of crime rate considered. Property crimes are better explained by socioeconomic variables (GDP per capita, GDP growth rate and percentage of population with high school and university degree), while demographic factors reveal important and significant influences, in particular for crimes against the person. These results are obtained using an instrumental variable approach that takes advantage of the dynamic properties of our dataset to control for both measurement errors in crime data and joint endogeneity of the explanatory variables

Identifying the parent-of-origin of de novo SNVs in schizophrenia

Several studies over the last few years have shown that newly arising (de novo) mutations contribute to the genetics of schizophrenia (SZ), autism (ASD) and other developmental disorders. The strongest evidence comes from studies of de novo Copy Number Variation (CNV), where the rate of new mutations is shown to be increased in cases when compared to controls [23, 24]. Research on de novo point mutations and small insertion-deletions (indels) has been more limited, but with the development of next-generation sequencing (NGS) technology, such studies are beginning to provide preliminary evidence that de novo single-nucleotide mutations (SNVs) might also increase risk of SZ and ASD [25, 26] Advanced paternal age is a major source of new mutations in human beings [27] and could thus be associated with increased risk for developing SZ, ASD or other developmental disorders. Indeed, advanced paternal age is found to be a risk factor for developing SZ and ASD in the offspring [28, 29] and new mutations related to advanced paternal age have been implicated as a cause of sporadic cases in several autosomal dominant diseases, some neurodevelopmental diseases, including SZ and ASD, and social functioning. New single-base substitutions occur at higher rates at males compared to females and this difference increases with paternal age. This is due to the fact that sperm cells go through a much higher number of cell divisions (~840 by the age of 50), which increases the risk for DNA copy errors in the male germ line [30] . By contrast, the female eggs (oocytes) undergo only 24 cell divisions and all but the last occur during foetal life. The aim of my project is to determine the parent-of-origin of de novo SNVs, using large samples of parent-offspring trios affected with schizophrenia (SZ). From whole exome sequencing of 618 Bulgarian proband-offspring trios affected, nearly 1000 de novo (SNVs or small indels) have been identified and from these, the parent-of-origin of at least 60% of the mutations (N=600) can be established. This project is contained in a main one that consists on the determination of the parental origin of different types of de novo mutations (SNVs, small indels and large CNVs).

Identifying the Role of Final Consumption in Structural Path Analysis: An Application to Water Uses

The complexity of the connexions within an economic system can only be reliably reflected in academic research if powerful methods are used. Researchers have used Structural Path Analysis (SPA) to capture not only the linkages within the production system but also the propagation of the effects into different channels of impacts. However, the SPA literature has restricted itself to showing the relations among sectors of production, while the connections between these sectors and final consumption have attracted little attention. In order to consider the complete set of channels involved, in this paper we propose a structural path method that endogenously incorporates not only sectors of production but also the final consumption of the economy. The empirical application comprises water usages, and analyses the dissemination of exogenous impacts into various channels of water consumption. The results show that the responsibility for water stress is imputed to different sectors and depends on the hypothesis used for the role played by final consumption in the model. This highlights the importance of consumers’ decisions in the determination of ecological impacts. Keywords: Input-Output Analysis, Structural Path Analysis, Final Consumption, Water uses.

Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

Background: Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements. Results: We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer- approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock Conclusion: Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.

Ischemic heart disease and primary care: identifying gender-related differences. An observational study

Background: Gender-related differences are seen in multiple aspects of both health and illness. Ischemic heart disease (IHD) is a pathology in which diagnostic, treatment and prognostic differences are seen between sexes, especially in the acute phase and in the hospital setting. The objective of the present study is to analyze whether there are differences between men and women when examining associated cardiovascular risk factors and secondary pharmacological prevention in the primary care setting. Methods: Retrospective descriptive observational study from January to December of 2006, including 1907 patients diagnosed with ischemic heart disease in the city of Lleida, Spain. The clinical data were obtained from computerized medical records and pharmaceutical records of medications dispensed in pharmacies with official prescriptions. Data was analyzed using bivariate descriptive statistical analysis as well as logistic regression. Results: There were no gender-related differences in screening percentages for arterial hypertension, diabetes, obesity, dyslipemia, and smoking. A greater percentage of women were hypertensive, obese and diabetic compared to men. However, men showed a tendency to achieve control targets more easily than women, with no statistically significant differences. In both sexes cardiovascular risk factors control was inadequate, between 10 and 50%. For secondary pharmaceutical prevention, the percentages of prescriptions were greater in men for anticoagulants, beta-blockers, lipid-lowering agents and angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers, with age group variations up to 10%. When adjusting by age and specific diagnoses, differences were maintained for anticoagulants and lipid-lowering agents. Conclusion: Screening of cardiovascular risk factors was similar in men and women with IHD. Although a greater percentage of women were hypertensive, diabetic or obese, their management of risk factors tended to be worse than men. Overall, a poor control of cardiovascular risk factors was noted. Taken as a whole, more men were prescribed secondary prevention drugs, with differences varying by age group and IHD diagnosis.

Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and pareto filters

Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the ethanol production in the fermentation of Saccharomyces cerevisiae.

Identifying variable gamma-ray sources through radio observations

We present preliminary results of a campaign undertaken with different radio interferometers to observe a sample of the most variable unidentified EGRET sources. We expect to detect which of the possible counterparts of the gamma-ray sources (any of the radio emitters in the field) varies in time with similar timescales as the gamma-ray variation. If the gamma-rays are produced in a jet-like source, as we have modelled theoretically, synchrotron emission is also expected at radio wavelengths. Such radio emission should appear variable in time and correlated with the gamma-ray variability.

Identifying Specific Cues and Contexts Related to Smoking Craving for the Development of Effective Virtual Environments

Craving is considered the main variable associated with relapse after smoking cessation. Cue Exposure Therapy (CET) consists of controlled and repeated exposure to drug-related cues with the aim of extinguishing craving responses. Some virtual reality (VR) environments, such as virtual bars or parties, have previously shown their efficacy as tools for eliciting smoking craving. However, in order to adapt this technology to smoking cessation interventions, there is a need for more diverse environments that enhance the probability of generalization of extinction in real life. The main objective of this study was to identify frequent situations that produce smoking craving, as well as detecting specific craving cues in those contexts. Participants were 154 smokers who responded to an ad hoc self-administered inventory for assessing craving level in 12 different situations. Results showed that having a drink in a bar/pub at night, after having lunch/dinner in a restaurant and having a coffee in a cafe or after lunch/dinner at home were reported as the most craving-inducing scenarios. Some differences were found with regard to participants' gender, age, and number of cigarettes smoked per day. Females, younger people, and heavier smokers reported higher levels of craving in most situations. In general, the most widely cited specific cues across the contexts were people smoking, having a coffee, being with friends, and having finished eating. These results are discussed with a view to their consideration in the design of valid and reliable VR environments that could be used in the treatment of nicotine addicts who wish to give up smoking.

Identifying pedagogical, technological and organizational barriers in virtual learning environments

Virtual learning environments are online spaces where learners interact with other learners, teachers, resources and the environment in itself. Although technology is meant to enhance the learning process, there are important issues regarding pedagogical and organizational aspects that must be addressed. In this paper we review the barriers detected in a virtual university which exclusively uses Internet as the main channel of communication, with no face-to-face requirements exceptthose related to final evaluation.