Innovation and economic performance of the firms in the service sector: relevant issues and open problems

This thesis is a collection of essays related to the topic of innovation in the service sector. The choice of this structure is functional to the purpose of single out some of the relevant issues and try to tackle them, revising first the state of the literature and then proposing a way forward. Three relevant issues has been therefore selected: (i) the definition of innovation in the service sector and the connected question of measurement of innovation; (ii) the issue of productivity in services; (iii) the classification of innovative firms in the service sector. Facing the first issue, chapter II shows how the initial width of the original Schumpeterian definition of innovation has been narrowed and then passed to the service sector form the manufacturing one in a reduce technological form. Chapter III tackle the issue of productivity in services, discussing the difficulties for measuring productivity in a context where the output is often immaterial. We reconstruct the dispute on the Baumol’s cost disease argument and propose two different ways to go forward in the research on productivity in services: redefining the output along the line of a characteristic approach; and redefining the inputs, particularly analysing which kind of input it’s worth saving. Chapter IV derives an integrated taxonomy of innovative service and manufacturing firms, using data coming from the 2008 CIS survey for Italy. This taxonomy is based on the enlarged definition of “innovative firm” deriving from the Schumpeterian definition of innovation and classify firms using a cluster analysis techniques. The result is the emergence of a four cluster solution, where firms are differentiated by the breadth of the innovation activities in which they are involved. Chapter 5 reports some of the main conclusions of each singular previous chapter and the points worth of further research in the future.

Statistical problems related to excitation threshold and reset value of membrane potentials

Die vorliegende Arbeit ist motiviert durch biologische Fragestellungen bezüglich des Verhaltens von Membranpotentialen in Neuronen. Ein vielfach betrachtetes Modell für spikende Neuronen ist das Folgende. Zwischen den Spikes verhält sich das Membranpotential wie ein Diffusionsprozess X der durch die SDGL dX_t= beta(X_t) dt+ sigma(X_t) dB_t gegeben ist, wobei (B_t) eine Standard-Brown'sche Bewegung bezeichnet. Spikes erklärt man wie folgt. Sobald das Potential X eine gewisse Exzitationsschwelle S überschreitet entsteht ein Spike. Danach wird das Potential wieder auf einen bestimmten Wert x_0 zurückgesetzt. In Anwendungen ist es manchmal möglich, einen Diffusionsprozess X zwischen den Spikes zu beobachten und die Koeffizienten der SDGL beta() und sigma() zu schätzen. Dennoch ist es nötig, die Schwellen x_0 und S zu bestimmen um das Modell festzulegen. Eine Möglichkeit, dieses Problem anzugehen, ist x_0 und S als Parameter eines statistischen Modells aufzufassen und diese zu schätzen. In der vorliegenden Arbeit werden vier verschiedene Fälle diskutiert, in denen wir jeweils annehmen, dass das Membranpotential X zwischen den Spikes eine Brown'sche Bewegung mit Drift, eine geometrische Brown'sche Bewegung, ein Ornstein-Uhlenbeck Prozess oder ein Cox-Ingersoll-Ross Prozess ist. Darüber hinaus beobachten wir die Zeiten zwischen aufeinander folgenden Spikes, die wir als iid Treffzeiten der Schwelle S von X gestartet in x_0 auffassen. Die ersten beiden Fälle ähneln sich sehr und man kann jeweils den Maximum-Likelihood-Schätzer explizit angeben. Darüber hinaus wird, unter Verwendung der LAN-Theorie, die Optimalität dieser Schätzer gezeigt. In den Fällen OU- und CIR-Prozess wählen wir eine Minimum-Distanz-Methode, die auf dem Vergleich von empirischer und wahrer Laplace-Transformation bezüglich einer Hilbertraumnorm beruht. Wir werden beweisen, dass alle Schätzer stark konsistent und asymptotisch normalverteilt sind. Im letzten Kapitel werden wir die Effizienz der Minimum-Distanz-Schätzer anhand simulierter Daten überprüfen. Ferner, werden Anwendungen auf reale Datensätze und deren Resultate ausführlich diskutiert.

Paleoclimate data-model comparison and the role of climate forcings over the past 1500 years

The past 1500 years provide a valuable opportunity to study the response of the climate system to external forcings. However, the integration of paleoclimate proxies with climate modeling is critical to improving the understanding of climate dynamics. In this paper, a climate system model and proxy records are therefore used to study the role of natural and anthropogenic forcings in driving the global climate. The inverse and forward approaches to paleoclimate data–model comparison are applied, and sources of uncertainty are identified and discussed. In the first of two case studies, the climate model simulations are compared with multiproxy temperature reconstructions. Robust solar and volcanic signals are detected in Southern Hemisphere temperatures, with a possible volcanic signal detected in the Northern Hemisphere. The anthropogenic signal dominates during the industrial period. It is also found that seasonal and geographical biases may cause multiproxy reconstructions to overestimate the magnitude of the long-term preindustrial cooling trend. In the second case study, the model simulations are compared with a coral δ18O record from the central Pacific Ocean. It is found that greenhouse gases, solar irradiance, and volcanic eruptions all influence the mean state of the central Pacific, but there is no evidence that natural or anthropogenic forcings have any systematic impact on El Niño–Southern Oscillation. The proxy climate relationship is found to change over time, challenging the assumption of stationarity that underlies the interpretation of paleoclimate proxies. These case studies demonstrate the value of paleoclimate data–model comparison but also highlight the limitations of current techniques and demonstrate the need to develop alternative approaches.

Effects of erythropoiesis-stimulating agents on fatigue- and anaemia-related symptoms in cancer patients: systematic review and meta-analyses of published and unpublished data.

Background:Erythropoiesis-stimulating agents (ESAs) reduce the need for red blood cell transfusions; however, they increase the risk of thromboembolic events and mortality. The impact of ESAs on quality of life (QoL) is controversial and led to different recommendations of medical societies and authorities in the USA and Europe. We aimed to critically evaluate and quantify the effects of ESAs on QoL in cancer patients.Methods:We included data from randomised controlled trials (RCTs) on the effects of ESAs on QoL in cancer patients. Randomised controlled trials were identified by searching electronic data bases and other sources up to January 2011. To reduce publication and outcome reporting biases, we included unreported results from clinical study reports. We conducted meta-analyses on fatigue- and anaemia-related symptoms measured with the Functional Assessment of Cancer Therapy-Fatigue (FACT-F) and FACT-Anaemia (FACT-An) subscales (primary outcomes) or other validated instruments.Results:We identified 58 eligible RCTs. Clinical study reports were available for 27% (4 out of 15) of the investigator-initiated trials and 95% (41 out of 43) of the industry-initiated trials. We excluded 21 RTCs as we could not use their QoL data for meta-analyses, either because of incomplete reporting (17 RCTs) or because of premature closure of the trial (4 RCTs). We included 37 RCTs with 10 581 patients; 21 RCTs were placebo controlled. Chemotherapy was given in 27 of the 37 RCTs. The median baseline haemoglobin (Hb) level was 10.1 g dl(-1); in 8 studies ESAs were stopped at Hb levels below 13 g dl(-1) and in 27 above 13 g dl(-1). For FACT-F, the mean difference (MD) was 2.41 (95% confidence interval (95% CI) 1.39-3.43; P<0.0001; 23 studies, n=6108) in all cancer patients and 2.81 (95% CI 1.73-3.90; P<0.0001; 19 RCTs, n=4697) in patients receiving chemotherapy, which was below the threshold (⩾3) for a clinically important difference (CID). Erythropoiesis-stimulating agents had a positive effect on anaemia-related symptoms (MD 4.09; 95% CI 2.37-5.80; P=0.001; 14 studies, n=2765) in all cancer patients and 4.50 (95% CI 2.55-6.45; P<0.0001; 11 RCTs, n=2436) in patients receiving chemotherapy, which was above the threshold (⩾4) for a CID. Of note, this effect persisted when we restricted the analysis to placebo-controlled RCTs in patients receiving chemotherapy. There was some evidence that the MDs for FACT-F were above the threshold for a CID in RCTs including cancer patients receiving chemotherapy with Hb levels below 12 g dl(-1) at baseline and in RCTs stopping ESAs at Hb levels above 13 g dl(-1). However, these findings for FACT-F were not confirmed when we restricted the analysis to placebo-controlled RCTs in patients receiving chemotherapy.Conclusions:In cancer patients, particularly those receiving chemotherapy, we found that ESAs provide a small but clinically important improvement in anaemia-related symptoms (FACT-An). For fatigue-related symptoms (FACT-F), the overall effect did not reach the threshold for a CID.British Journal of Cancer advance online publication, 17 April 2014; doi:10.1038/bjc.2014.171 www.bjcancer.com.

Hormonal Contraception and the Risk of HIV Acquisition: An Individual Participant Data Meta-analysis.

BACKGROUND Observational studies of a putative association between hormonal contraception (HC) and HIV acquisition have produced conflicting results. We conducted an individual participant data (IPD) meta-analysis of studies from sub-Saharan Africa to compare the incidence of HIV infection in women using combined oral contraceptives (COCs) or the injectable progestins depot-medroxyprogesterone acetate (DMPA) or norethisterone enanthate (NET-EN) with women not using HC. METHODS AND FINDINGS Eligible studies measured HC exposure and incident HIV infection prospectively using standardized measures, enrolled women aged 15-49 y, recorded ≥15 incident HIV infections, and measured prespecified covariates. Our primary analysis estimated the adjusted hazard ratio (aHR) using two-stage random effects meta-analysis, controlling for region, marital status, age, number of sex partners, and condom use. We included 18 studies, including 37,124 women (43,613 woman-years) and 1,830 incident HIV infections. Relative to no HC use, the aHR for HIV acquisition was 1.50 (95% CI 1.24-1.83) for DMPA use, 1.24 (95% CI 0.84-1.82) for NET-EN use, and 1.03 (95% CI 0.88-1.20) for COC use. Between-study heterogeneity was mild (I2 < 50%). DMPA use was associated with increased HIV acquisition compared with COC use (aHR 1.43, 95% CI 1.23-1.67) and NET-EN use (aHR 1.32, 95% CI 1.08-1.61). Effect estimates were attenuated for studies at lower risk of methodological bias (compared with no HC use, aHR for DMPA use 1.22, 95% CI 0.99-1.50; for NET-EN use 0.67, 95% CI 0.47-0.96; and for COC use 0.91, 95% CI 0.73-1.41) compared to those at higher risk of bias (pinteraction = 0.003). Neither age nor herpes simplex virus type 2 infection status modified the HC-HIV relationship. CONCLUSIONS This IPD meta-analysis found no evidence that COC or NET-EN use increases women's risk of HIV but adds to the evidence that DMPA may increase HIV risk, underscoring the need for additional safe and effective contraceptive options for women at high HIV risk. A randomized controlled trial would provide more definitive evidence about the effects of hormonal contraception, particularly DMPA, on HIV risk.

X-ray fluorescence data (calcium and iron), bulk organic d13C, and dinoflagellate cysts of ODP Hole 189-1172D

The 'Paleocene/Eocene Thermal Maximum' or PETM (~55 Ma) was associated with dramatic warming of the oceans and atmosphere, pronounced changes in ocean circulation and chemistry, and upheaval of the global carbon cycle. Many relatively complete PETM sequences have by now been reported from around the world, but most are from ancient low- to midlatitude sites. ODP Leg 189 in the Tasman Sea recovered sediments from this critical phase in Earth history at Sites 1171 and 1172, potentially representing the southernmost PETM successions ever encountered (at ~70° to 65° S paleolatitude). Downhole and core logging data, in combination with dinoflagellate cyst biostratigraphy, magneto-stratigraphy, and stable isotope geochemistry indicate that the sequences at both sites were deposited in a high accumulation-rate, organic rich, marginal marine setting. Furthermore, Site 1172 indeed contains a fairly complete P-E transition, whereas at Site 1171, only the lowermost Eocene is recovered. However, at Site 1172, the typical PETM-indicative acme of the dinocyst Apectodinium was not recorded. We conclude that unfortunately, the critical latest Paleocene and PETM intervals are missing at Site 1172. We relate the missing section to a sea level driven hiatus and/or condensed section and recovery problems. Nevertheless, our integrated records provide a first-ever portrait of the trend toward, and aftermath of, the PETM in a marginal marine, southern high-latitude setting.

Composition of post-Jurassic deposits from the Northwest Pacific and the Galapagos Rift, data of DSDP Legs 62, 65, and 70

The monogragh contains results of mineralogicai and geochemical studies of Mesozoic and Cenozoic deposits from the Pacific Ocean collected during Deep Sea Drilling Project. Special attention is paid on the aspects of geochemical history of post-Jurassic sedimentation in the central part of the Northwest Pacific, detailed characteristics of the main stages of sedimentary evolution are given: Early Cretaceons (protooceanic), Late Cretaceons (transitional) and Cenozoic (oceanic). Results of mineralogical and geochemical studies of hydrothermal deposits from the Galapagos Rift are given as well.

Chapter 2 On the usage of the measurements of geographical concentration and specialization with areal data

Measures have been developed to understand tendencies in the distribution of economic activity. The merits of these measures are in the convenience of data collection and processing. In this interim report, investigating the property of such measures to determine the geographical spread of economic activities, we summarize the merits and limitations of measures, and make clear that we must apply caution in their usage. As a first trial to access areal data, this project focus on administrative areas, not on point data and input-output data. Firm level data is not within the scope of this article. The rest of this article is organized as follows. In Section 2, we touch on the the limitations and problems associated with the measures and areal data. Specific measures are introduced in Section 3, and applied in Section 4. The conclusion summarizes the findings and discusses future work.

A method to incorporate the effect of taxonomic uncertainty on multivariate analyses of ecological data

Researchers in ecology commonly use multivariate analyses (e.g. redundancy analysis, canonical correspondence analysis, Mantel correlation, multivariate analysis of variance) to interpret patterns in biological data and relate these patterns to environmental predictors. There has been, however, little recognition of the errors associated with biological data and the influence that these may have on predictions derived from ecological hypotheses. We present a permutational method that assesses the effects of taxonomic uncertainty on the multivariate analyses typically used in the analysis of ecological data. The procedure is based on iterative randomizations that randomly re-assign non identified species in each site to any of the other species found in the remaining sites. After each re-assignment of species identities, the multivariate method at stake is run and a parameter of interest is calculated. Consequently, one can estimate a range of plausible values for the parameter of interest under different scenarios of re-assigned species identities. We demonstrate the use of our approach in the calculation of two parameters with an example involving tropical tree species from western Amazonia: 1) the Mantel correlation between compositional similarity and environmental distances between pairs of sites, and; 2) the variance explained by environmental predictors in redundancy analysis (RDA). We also investigated the effects of increasing taxonomic uncertainty (i.e. number of unidentified species), and the taxonomic resolution at which morphospecies are determined (genus-resolution, family-resolution, or fully undetermined species) on the uncertainty range of these parameters. To achieve this, we performed simulations on a tree dataset from southern Mexico by randomly selecting a portion of the species contained in the dataset and classifying them as unidentified at each level of decreasing taxonomic resolution. An analysis of covariance showed that both taxonomic uncertainty and resolution significantly influence the uncertainty range of the resulting parameters. Increasing taxonomic uncertainty expands our uncertainty of the parameters estimated both in the Mantel test and RDA. The effects of increasing taxonomic resolution, however, are not as evident. The method presented in this study improves the traditional approaches to study compositional change in ecological communities by accounting for some of the uncertainty inherent to biological data. We hope that this approach can be routinely used to estimate any parameter of interest obtained from compositional data tables when faced with taxonomic uncertainty.

A Comparison of different Uncertainty Activation Cross-Section Data Libraries: Application to the Prediction Uncertainty in Tritium Production

T actitivity in LiPb LiPb mock-up material irradiated in Frascati: measurement and MCNP results

A Comparison of Sensitivity/Uncertainty Methodologies for the Tritium Production in the HFTM/IFMIF Specimen Cells and measurements in Tritium activity in HCLL TBM mock-up LiPb

The prediction of the tritium production is required for handling procedures of samples, safety&maintenance and licensing of the International Fusion Materials Irradiation Facility (IFMIF).

Nuclear Data Uncertainty Propagation to Reactivity Coefficients of a Sodium Fast Reactor

The assessment of the uncertainty levels on the design and safety parameters for the innovative European Sodium Fast Reactor (ESFR) is mandatory. Some of these relevant safety quantities are the Doppler and void reactivity coefficients, whose uncertainties are quantified. Besides, the nuclear reaction data where an improvement will certainly benefit the design accuracy are identified. This work has been performed with the SCALE 6.1 codes suite and its multigroups cross sections library based on ENDF/B-VII.0 evaluation.

Development of a methodology for nuclear data uncertainty propagation on isotopic evolution calculations for advanced nuclear systems

Una apropiada evaluación de los márgenes de seguridad de una instalación nuclear, por ejemplo, una central nuclear, tiene en cuenta todas las incertidumbres que afectan a los cálculos de diseño, funcionanmiento y respuesta ante accidentes de dicha instalación. Una fuente de incertidumbre son los datos nucleares, que afectan a los cálculos neutrónicos, de quemado de combustible o activación de materiales. Estos cálculos permiten la evaluación de las funciones respuesta esenciales para el funcionamiento correcto durante operación, y también durante accidente. Ejemplos de esas respuestas son el factor de multiplicación neutrónica o el calor residual después del disparo del reactor. Por tanto, es necesario evaluar el impacto de dichas incertidumbres en estos cálculos. Para poder realizar los cálculos de propagación de incertidumbres, es necesario implementar metodologías que sean capaces de evaluar el impacto de las incertidumbres de estos datos nucleares. Pero también es necesario conocer los datos de incertidumbres disponibles para ser capaces de manejarlos. Actualmente, se están invirtiendo grandes esfuerzos en mejorar la capacidad de analizar, manejar y producir datos de incertidumbres, en especial para isótopos importantes en reactores avanzados. A su vez, nuevos programas/códigos están siendo desarrollados e implementados para poder usar dichos datos y analizar su impacto. Todos estos puntos son parte de los objetivos del proyecto europeo ANDES, el cual ha dado el marco de trabajo para el desarrollo de esta tesis doctoral. Por tanto, primero se ha llevado a cabo una revisión del estado del arte de los datos nucleares y sus incertidumbres, centrándose en los tres tipos de datos: de decaimiento, de rendimientos de fisión y de secciones eficaces. A su vez, se ha realizado una revisión del estado del arte de las metodologías para la propagación de incertidumbre de estos datos nucleares. Dentro del Departamento de Ingeniería Nuclear (DIN) se propuso una metodología para la propagación de incertidumbres en cálculos de evolución isotópica, el Método Híbrido. Esta metodología se ha tomado como punto de partida para esta tesis, implementando y desarrollando dicha metodología, así como extendiendo sus capacidades. Se han analizado sus ventajas, inconvenientes y limitaciones. El Método Híbrido se utiliza en conjunto con el código de evolución isotópica ACAB, y se basa en el muestreo por Monte Carlo de los datos nucleares con incertidumbre. En esta metodología, se presentan diferentes aproximaciones según la estructura de grupos de energía de las secciones eficaces: en un grupo, en un grupo con muestreo correlacionado y en multigrupos. Se han desarrollado diferentes secuencias para usar distintas librerías de datos nucleares almacenadas en diferentes formatos: ENDF-6 (para las librerías evaluadas), COVERX (para las librerías en multigrupos de SCALE) y EAF (para las librerías de activación). Gracias a la revisión del estado del arte de los datos nucleares de los rendimientos de fisión se ha identificado la falta de una información sobre sus incertidumbres, en concreto, de matrices de covarianza completas. Además, visto el renovado interés por parte de la comunidad internacional, a través del grupo de trabajo internacional de cooperación para evaluación de datos nucleares (WPEC) dedicado a la evaluación de las necesidades de mejora de datos nucleares mediante el subgrupo 37 (SG37), se ha llevado a cabo una revisión de las metodologías para generar datos de covarianza. Se ha seleccionando la actualización Bayesiana/GLS para su implementación, y de esta forma, dar una respuesta a dicha falta de matrices completas para rendimientos de fisión. Una vez que el Método Híbrido ha sido implementado, desarrollado y extendido, junto con la capacidad de generar matrices de covarianza completas para los rendimientos de fisión, se han estudiado diferentes aplicaciones nucleares. Primero, se estudia el calor residual tras un pulso de fisión, debido a su importancia para cualquier evento después de la parada/disparo del reactor. Además, se trata de un ejercicio claro para ver la importancia de las incertidumbres de datos de decaimiento y de rendimientos de fisión junto con las nuevas matrices completas de covarianza. Se han estudiado dos ciclos de combustible de reactores avanzados: el de la instalación europea para transmutación industrial (EFIT) y el del reactor rápido de sodio europeo (ESFR), en los cuales se han analizado el impacto de las incertidumbres de los datos nucleares en la composición isotópica, calor residual y radiotoxicidad. Se han utilizado diferentes librerías de datos nucleares en los estudios antreriores, comparando de esta forma el impacto de sus incertidumbres. A su vez, mediante dichos estudios, se han comparando las distintas aproximaciones del Método Híbrido y otras metodologías para la porpagación de incertidumbres de datos nucleares: Total Monte Carlo (TMC), desarrollada en NRG por A.J. Koning y D. Rochman, y NUDUNA, desarrollada en AREVA GmbH por O. Buss y A. Hoefer. Estas comparaciones demostrarán las ventajas del Método Híbrido, además de revelar sus limitaciones y su rango de aplicación. ABSTRACT For an adequate assessment of safety margins of nuclear facilities, e.g. nuclear power plants, it is necessary to consider all possible uncertainties that affect their design, performance and possible accidents. Nuclear data are a source of uncertainty that are involved in neutronics, fuel depletion and activation calculations. These calculations can predict critical response functions during operation and in the event of accident, such as decay heat and neutron multiplication factor. Thus, the impact of nuclear data uncertainties on these response functions needs to be addressed for a proper evaluation of the safety margins. Methodologies for performing uncertainty propagation calculations need to be implemented in order to analyse the impact of nuclear data uncertainties. Nevertheless, it is necessary to understand the current status of nuclear data and their uncertainties, in order to be able to handle this type of data. Great eórts are underway to enhance the European capability to analyse/process/produce covariance data, especially for isotopes which are of importance for advanced reactors. At the same time, new methodologies/codes are being developed and implemented for using and evaluating the impact of uncertainty data. These were the objectives of the European ANDES (Accurate Nuclear Data for nuclear Energy Sustainability) project, which provided a framework for the development of this PhD Thesis. Accordingly, first a review of the state-of-the-art of nuclear data and their uncertainties is conducted, focusing on the three kinds of data: decay, fission yields and cross sections. A review of the current methodologies for propagating nuclear data uncertainties is also performed. The Nuclear Engineering Department of UPM has proposed a methodology for propagating uncertainties in depletion calculations, the Hybrid Method, which has been taken as the starting point of this thesis. This methodology has been implemented, developed and extended, and its advantages, drawbacks and limitations have been analysed. It is used in conjunction with the ACAB depletion code, and is based on Monte Carlo sampling of variables with uncertainties. Different approaches are presented depending on cross section energy-structure: one-group, one-group with correlated sampling and multi-group. Differences and applicability criteria are presented. Sequences have been developed for using different nuclear data libraries in different storing-formats: ENDF-6 (for evaluated libraries) and COVERX (for multi-group libraries of SCALE), as well as EAF format (for activation libraries). A revision of the state-of-the-art of fission yield data shows inconsistencies in uncertainty data, specifically with regard to complete covariance matrices. Furthermore, the international community has expressed a renewed interest in the issue through the Working Party on International Nuclear Data Evaluation Co-operation (WPEC) with the Subgroup (SG37), which is dedicated to assessing the need to have complete nuclear data. This gives rise to this review of the state-of-the-art of methodologies for generating covariance data for fission yields. Bayesian/generalised least square (GLS) updating sequence has been selected and implemented to answer to this need. Once the Hybrid Method has been implemented, developed and extended, along with fission yield covariance generation capability, different applications are studied. The Fission Pulse Decay Heat problem is tackled first because of its importance during events after shutdown and because it is a clean exercise for showing the impact and importance of decay and fission yield data uncertainties in conjunction with the new covariance data. Two fuel cycles of advanced reactors are studied: the European Facility for Industrial Transmutation (EFIT) and the European Sodium Fast Reactor (ESFR), and response function uncertainties such as isotopic composition, decay heat and radiotoxicity are addressed. Different nuclear data libraries are used and compared. These applications serve as frameworks for comparing the different approaches of the Hybrid Method, and also for comparing with other methodologies: Total Monte Carlo (TMC), developed at NRG by A.J. Koning and D. Rochman, and NUDUNA, developed at AREVA GmbH by O. Buss and A. Hoefer. These comparisons reveal the advantages, limitations and the range of application of the Hybrid Method.