An R package for the integrated analysis of metabolomics and spectral data

Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.

What works best for getting the unemployed back to work: employment services or small-business assistance programs? evidence from Romania

Recent empirical evidence has found that employment services and small-business assistance programmes are often successful at getting the unemployed back to work. Â One important concern of policy makers is to decide which of these two programmes is more effective and for whom. Â Using unusually rich (for transition economies) survey data and matching methods, I evaluate the relative effectiveness of these two programmes in Romania. Â While I find that employment services (ES) are, on average, more successful than a small-business assistance programme (SBA), estimation of heterogeneity effects reveals that, compared to non-participation, ES are effective for workers with little access to informal search channels, and SBA works for less-qualified workers and those living in rural areas. Â When comparing ES to SBA, I find that ES tend to be more efficient than SBA for workers without a high-school degree, and that the opposite holds for the more educated workers.

Addressing Sea Surface Salinity retrieval at different spatial resolution. Feasibility study using OCCAM data within SEPS simulator and L2 processor tools

Projecte de recerca elaborat a partir d’una estada a la National Oceanography Centre of Southampton (NOCS), Gran Bretanya, entre maig i juliol del 2006. La possibilitat d’obtenir una estimació precissa de la salinitat marina (SSS) és important per a investigar i predir l’extensió del fenòmen del canvi climàtic. La missió Soil Moisture and Ocean Salinity (SMOS) va ser seleccionada per l’Agència Espacial Europea (ESA) per a obtenir mapes de salinitat de la superfície marina a escala global i amb un temps de revisita petit. Abans del llençament de SMOS es preveu l’anàlisi de la variabilitat horitzontal de la SSS i del potencial de les dades recuperades a partir de mesures de SMOS per a reproduir comportaments oceanogràfics coneguts. L’objectiu de tot plegat és emplenar el buit existent entre les fonts de dades d’entrada/auxiliars fiables i les eines desenvolupades per a simular i processar les dades adquirides segons la configuració de SMOS. El SMOS End-to-end Performance Simulator (SEPS) és un simulador adhoc desenvolupat per la Universitat Politècnica de Catalunya (UPC) per a generar dades segons la configuració de SMOS. Es va utilitzar dades d’entrada a SEPS procedents del projecte Ocean Circulation and Climate Advanced Modeling (OCCAM), utilitzat al NOCS, a diferents resolucions espacials. Modificant SEPS per a poder fer servir com a entrada les dades OCCAM es van obtenir dades de temperatura de brillantor simulades durant un mes amb diferents observacions ascendents que cobrien la zona seleccionada. Les tasques realitzades durant l’estada a NOCS tenien la finalitat de proporcionar una tècnica fiable per a realitzar la calibració externa i per tant cancel•lar el bias, una metodologia per a promitjar temporalment les diferents adquisicions durant les observacions ascendents, i determinar la millor configuració de la funció de cost abans d’explotar i investigar les posibiltats de les dades SEPS/OCCAM per a derivar la SSS recuperada amb patrons d’alta resolució.

Innovation sources and productivity in Catalonian firms: a quantile regression analysis

This paper explores the effects of two main sources of innovation -intramural and external R&D- on the productivity level in a sample of 3,267 Catalonian firms. The data set used is based on the official innovation survey of Catalonia which was a part of the Spanish sample of CIS4, covering the years 2002-2004. We compare empirical results by applying usual OLS and quantile regression techniques both in manufacturing and services industries. In quantile regression, results suggest different patterns at both innovation sources as we move across conditional quantiles. The elasticity of intramural R&D activities on productivity decreased when we move up the high productivity levels both in manufacturing and services sectors, while the effects of external R&D rise in high-technology industries but are more ambiguous in low-technology and knowledge-intensive services. JEL codes: O300, C100, O140. Keywords: Innovation sources, R&D, Productivity, Quantile regression

Innovation, R&D spillovers and productivity: the role of knowledge-intensive services

This paper analyses the performance of companies’ R&D and innovation and the effects of intra- and inter-industry R&D spillover on firms’ productivity in Catalonia. The paper deals simultaneously with the performance of manufacturing and service firms, with the aim of highlighting the growing role of knowledge-intensive services in promoting innovation and productivity gains. We find that intra-industry R&D spillovers have an important effect on the productivity level of manufacturing firms, and the inter-industrial R&D spillovers related to computer and software services also play an important role, especially in high-tech manufacturing industries. The main conclusion is that the traditional classification of manufactured goods and services no longer makes sense in the ‘knowledge economy’ and in Catalonia the regional policy makers will have to design policies that favour inter-industrial R&D flows, especially from high-tech services.

Innovation sources and productivity: a quantile regression analysis

This paper explores the effects of two main sources of innovation —intramural and external R&D— on the productivity level in a sample of 3,267 Catalan firms. The data set used is based on the official innovation survey of Catalonia which was a part of the Spanish sample of CIS4, covering the years 2002-2004. We compare empirical results by applying usual OLS and quantile regression techniques both in manufacturing and services industries. In quantile regression, results suggest different patterns at both innovation sources as we move across conditional quantiles. The elasticity of intramural R&D activities on productivity decreased when we move up the high productivity levels both in manufacturing and services sectors, while the effects of external R&D rise in high-technology industries but are more ambiguous in low-technology and services industries.

Finance and Balanced Growth

The Uzawa (1961) theorem applied to finance and growthsuggests that a long-run positive correlation between financial efficiency and depth is only present when variations in the extent of access to financial services are considered. Improvements in financial efficiency can lead to new capital augmenting technologies along the balanced path, but only improvements in financial efficiency directed towards labor can change the rate of growth in the long-run. These findings suggest ways to understand some of the more nuanced relationships between finance and growth observed in the data and point in a number of directions for future research.

Authoritarian Responses to Foreign Pressure: Spending, Repression, and Sanctions

This paper explores how international sanctions affect authoritarian rulers’ decisions concerning repression and public spending composition, and how different authoritarian rulers respond to foreign pressure. If sanctions are assumed to increase the price of loyalty to the regime, then rulers whose budgets are not severely constrained by sanctions will tend to increase spending in those categories that most benefit their core support groups. In contrast, when constraints are severe due to reduced aid and trade, dictators are expected to greatly increase their levels of repression. Using data on regime types, public expenditures and spending composition (1970–2000) as well as on repression levels (1976–2001), we show that the empirical patterns conform well to our theoretical expectations. Single-party regimes, when targeted by sanctions, increase spending on subsidies and transfers which largely benefit more substantial sectors of the population and especially the urban classes. Likewise, military regimes increase their expenditures on goods and services, which include military equipment and soldiers’ and officers’ wages. Conversely, personalist regimes reduce spending in all categories, especially capital expenditures, while increasing repression much more than other regime types when targeted by sanctions.

Innovation sources and productivity in Catalonian firms: a quantile regression analysis

This paper explores the effects of two main sources of innovation - intramural and external R&D— on the productivity level in a sample of 3,267 Catalonian firms. The data set used is based on the official innovation survey of Catalonia which was a part of the Spanish sample of CIS4, covering the years 2002-2004. We compare empirical results by applying usual OLS and quantile regression techniques both in manufacturing and services industries. In quantile regression, results suggest different patterns at both innovation sources as we move across conditional quantiles. The elasticity of intramural R&D activities on productivity decreased when we move up the high productivity levels both in manufacturing and services sectors, while the effects of external R&D rise in high-technology industries but are more ambiguous in low-technology and knowledge-intensive services. JEL codes: O300, C100, O140 Keywords: Innovation sources, R&D, Productivity, Quantile Regression

R&D cooperation between Spanish firms and scientific partners: what is the role of tertiary education?

This paper explores the factors that determine firm’s R&D cooperation with different partners, paying special attention on the role of tertiary education (degree and PhDs level) in facilitating the connection between the firms and the to scientific bodies (technology centres, public research centres and universities). Here, we attempt to answer two questions. First, are innovative firms that carry out internal and external R&D activities more likely to cooperate on R&D projects with other partners? Second, do Spanish innovative firms with a high participation of researchers with degrees or PhDs tend to cooperate more with scientific partners? To answer both questions we apply a three-dimensional approach on a firm level Panel Data with a sample of 4.998 manufacturing and services Spanish firms. First, we run a complementary test between external R&D acquisition and skilled research workers and find that firms which carry out external R&D activities obtain a greater return on R&D cooperation when they have skilled workers in R&D, especially in high-tech manufactures and KIS services. Second, we carry out a 2-step tobit model to estimate, in the first stage, the determinants that explain whether Spanish innovative firms cooperate or not; and in the second stage the factors that affect the choice of partners. And third, we apply an ordered probit model to test the marginal effects of explanatory variables on the different partners. Here we contrast some of the most interesting empirical hypotheses of previous studies, and which emphasize the role of employees with degrees and PhDs in facilitating cooperative R&D between firms and scientific partners.

IPH response to DSD Urban Regeneration and Community Development Policy Framework Consultation

The Urban Regeneration and Community Development Policy Framework for Northern Ireland sets out for DSD and its partners, clear priorities for urban regeneration and community development programmes, both before and after the operational responsibility for these is transferred to councils under the reform of local government. Four policy objectives have been developed, which will focus on the underlying structural problems in urban areas and also help strengthen community development throughout Northern Ireland. The policy objectives are as follows: Policy Objective 1 – To tackle area-based deprivation: Policy Objective 2 – To strengthen the competitiveness of our towns and cities: Policy Objective 3 – To improve linkages between areas of need and areas of opportunity: and Policy Objective 4 –To develop more cohesive and engaged communities. Key points from IPH response Urban regeneration and community development provide a basis for addressing the social determinants of health and reducing inequalities in health. This policy framework presents an opportunity for coherence and complementarity with ‘Fit and Well - Changing Lives’ as part of government’s overall approach to tackling health inequalities. It is now well established that a focus on early years’ interventions and family support services yields significant returns, so prioritising action in these areas is essential. Defined action plans on child poverty are essential if this policy framework is to make a real and lasting difference in deprived urban areas. Development of the environmental infrastructure to improve health in deprived areas should be supported by well-planned monitoring and evaluation. Linking the policy framework to economic development and local community plans will enhance effectiveness in the areas of education, job creation, commercial investment and access to services, which in turn are critical for the economic growth and stability of urban communities. Community profile data and health intelligence (as available through IPH Health Well) could usefully inform central and local government in terms of resource allocation and targeted service delivery.

IPH response to the HIQA consultation on the National Demographic Dataset and Guidance for use in health and social care settings in Ireland

The remit of the Institute of Public Health in Ireland (IPH) is to promote cooperation for public health between Northern Ireland and the Republic of Ireland in the areas of research and information, capacity building and policy advice. Our approach is to support Departments of Health and their agencies in both jurisdictions, and maximise the benefits of all-island cooperation to achieve practical benefits for people in Northern Ireland and the Republic of Ireland. IPH have previously responded to consultations to the Department of Health’s Discussion Paper on the Proposed Health Information Bill (June 2008), the Health Information and Quality Authority on their Corporate Plan (Oct 2007), and the Road Safety Authority of Ireland Road Safety Strategy (Jul 2012). IPH supports the development of a national standard demographic dataset for use within the health and social care services. Provided necessary safeguards are put in place (such as ethics and data protection) and the purpose of collecting the information is fully explained to subjects, mandatory provision of a minimum demographic dataset is usually the best way to achieve the necessary coverage and data quality. Demographic information is needed in several forms to support the public health function: Detailed aggregated information for comparison to population counts in order to assess equity of access to healthcare as well as examining population patterns and trends in morbidity and mortality Accurate demographic information for the surveillance of infectious disease outbreaks, monitoring vaccination programmes, setting priorities for public health interventions Linked to other data outside of health and social care such as population data, survey data, and longitudinal studies for research and analysis purposes.   Identify and address public health issues to tackle health inequalities, and to monitor the success of such efforts to tackle them.

R&D cooperation between Spanish firms and scientific partners: what is the role of tertiary education?

This paper explores the factors that determine firm’s R&D cooperation with different partners, paying special attention on the role of tertiary education (degree and PhDs level) in facilitating the connection between the firms and the to scientific bodies (technology centres, public research centres and universities). Here, we attempt to answer two questions. First, are innovative firms that carry out internal and external R&D activities more likely to cooperate on R&D projects with other partners? Second, do Spanish innovative firms with a high participation of researchers with degrees or PhDs tend to cooperate more with scientific partners? To answer both questions we apply a three-dimensional approach on a firm level Panel Data with a sample of 4.998 manufacturing and services Spanish firms. First, we run a complementary test between external R&D acquisition and skilled research workers and find that firms which carry out external R&D activities obtain a greater return on R&D cooperation when they have skilled workers in R&D, especially in high-tech manufactures and KIS services. Second, we carry out a 2-step tobit model to estimate, in the first stage, the determinants that explain whether Spanish innovative firms cooperate or not; and in the second stage the factors that affect the choice of partners. And third, we apply an ordered probit model to test the marginal effects of explanatory variables on the different partners. Here we contrast some of the most interesting empirical hypotheses of previous studies, and which emphasize the role of employees with degrees and PhDs in facilitating cooperative R&D between firms and scientific partners. JEL classification: O31, O33, O38. Key words: Determinants R&D cooperation, industry-university flows, PhD research workers.

High Growth Firms and Innovation: an empirical analysis for Spanish firms

This paper analyzes the effect of firms’ innovation activities on their growth performance. In particular, we observe how important innovation is for high-growth firms (HGFs) for an extensive sample of Spanish manufacturing and services firms. The panel data used comprises diverse waves of Spanish CIS over the the period 2004-2008. First, a probit analysis determines whether innovation affects the probability of being a high-growth firm. And second, a quantile regression technique is applied to explore the determinants and characteristics of specific groups of firms (manufacturing versus service firms and high-tech versus low-tech firms). It is revealed that R&D plays a significant role in the probability of becoming a HGF. Investment in internal and external R&D per employee has a positive impact on firm growth (although internal R&D presents a significant impact in the last quantiles, external R&D is significant up to the median). Furthermore, we show evidence that there is a positive impact of employment (sales) growth on the sales (employment) growth. Keywords: high-growth firms, firm growth, innovation activity JEL Classifications: L11, L25, O30

Gene expression databases and data mining.

The DNA microarray technology has arguably caught the attention of the worldwide life science community and is now systematically supporting major discoveries in many fields of study. The majority of the initial technical challenges of conducting experiments are being resolved, only to be replaced with new informatics hurdles, including statistical analysis, data visualization, interpretation, and storage. Two systems of databases, one containing expression data and one containing annotation data are quickly becoming essential knowledge repositories of the research community. This present paper surveys several databases, which are considered "pillars" of research and important nodes in the network. This paper focuses on a generalized workflow scheme typical for microarray experiments using two examples related to cancer research. The workflow is used to reference appropriate databases and tools for each step in the process of array experimentation. Additionally, benefits and drawbacks of current array databases are addressed, and suggestions are made for their improvement.