The roots of success: industrial growth in Italy reconsidered, 1911- 1951

This article reconsiders the growth of Italian industry from the First World War to the eve of the economic miracle, with the aid of sector-specific new value-added series, at three different price-bases. The new estimates reduce growth during the First World War, making the Italian case comparable to the other belligerent countries, while improving the performance of the 1920s. The 1929 crisis looks more profound than before, while the recovery after 1933 is now stronger. During the 1920s and the 1930s, a significant shift from traditional to more advanced activities took place: when confronted with the rest of Europe, the interwar period was a relative success, which laid the ground for the following economic boom.

Modeling the biophysical impacts of global change in mountain biosphere reserves

Mountains and mountain societies provide a wide range of goods and services to humanity, but they are particularly sensitive to the effects of global environmental change. Thus, the definition of appropriate management regimes that maintain the multiple functions of mountain regions in a time of greatly changing climatic, economic, and societal drivers constitutes a significant challenge. Management decisions must be based on a sound understanding of the future dynamics of these systems. The present article reviews the elements required for an integrated effort to project the impacts of global change on mountain regions, and recommends tools that can be used at 3 scientific levels (essential, improved, and optimum). The proposed strategy is evaluated with respect to UNESCO's network of Mountain Biosphere Reserves (MBRs), with the intention of implementing it in other mountain regions as well. First, methods for generating scenarios of key drivers of global change are reviewed, including land use/land cover and climate change. This is followed by a brief review of the models available for projecting the impacts of these scenarios on (1) cryospheric systems, (2) ecosystem structure and diversity, and (3) ecosystem functions such as carbon and water relations. Finally, the cross-cutting role of remote sensing techniques is evaluated with respect to both monitoring and modeling efforts. We conclude that a broad range of techniques is available for both scenario generation and impact assessments, many of which can be implemented without much capacity building across many or even most MBRs. However, to foster implementation of the proposed strategy, further efforts are required to establish partnerships between scientists and resource managers in mountain areas.

Audit report on America's Agricultural Industrial Heritage Landscape Inc. d/b/a Silos and Smokestacks National Heritage Area, Independent Auditor's Reports, Financial Statements and Supplementary Information, Schedule of Findings and Questioned Costs, December 31st, 2003 & 2004

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Genetic and genomic analysis modeling of germline c-MYC overexpression and cancer susceptibility

Background: Germline genetic variation is associated with the differential expression of many human genes. The phenotypic effects of this type of variation may be important when considering susceptibility to common genetic diseases. Three regions at 8q24 have recently been identified to independently confer risk of prostate cancer. Variation at 8q24 has also recently been associated with risk of breast and colorectal cancer. However, none of the risk variants map at or relatively close to known genes, with c-MYC mapping a few hundred kilobases distally. Results: This study identifies cis-regulators of germline c-MYC expression in immortalized lymphocytes of HapMap individuals. Quantitative analysis of c-MYC expression in normal prostate tissues suggests an association between overexpression and variants in Region 1 of prostate cancer risk. Somatic c-MYC overexpression correlates with prostate cancer progression and more aggressive tumor forms, which was also a pathological variable associated with Region 1. Expression profiling analysis and modeling of transcriptional regulatory networks predicts a functional association between MYC and the prostate tumor suppressor KLF6. Analysis of MYC/Myc-driven cell transformation and tumorigenesis substantiates a model in which MYC overexpression promotes transformation by down-regulating KLF6. In this model, a feedback loop through E-cadherin down-regulation causes further transactivation of c-MYC.Conclusion: This study proposes that variation at putative 8q24 cis-regulator(s) of transcription can significantly alter germline c-MYC expression levels and, thus, contribute to prostate cancer susceptibility by down-regulating the prostate tumor suppressor KLF6 gene.

Informed Control Over Inputs and Extent of Industrial Processing, June 2005

Stylized facts regarding the industrial process include emphases on obtaining information about and control over the quality of raw materials. We provide a model that establishes conditions under which informed control involves ensuring uniformity in inputs and increased uniformity encourages more extensive processing. We show when the Boltzmann-Shannon entropy statistic is an appropriate measure of uniformity.

Aplicación de buenas prácticas para la mejora de la calidad de los trabajos fin de grado en Ing. en Diseño Industrial

El trabajo presentado en esta comunicación se enmarca en un proyecto financiado por la Secretaría de Estado de Universidades, Ministerio de Educación Cultura y Deporte en su Programa de Estudios y Análisis, mejora de la calidad de la enseñanza superior y de la actividad del profesorado universitario en el Eje de Nuevos avances y determinación del impacto de las misiones universitarias, Modalidad de Trabajos de análisis, lideradopor la Universitat Pompeu Fabra y en el que participan docentes de las universidades de Valladolid, Cádiz, Las Palmas de Gran Canaria, Sevilla, Autónoma de Barcelona, Carlos III de Madrid y Universidat Oberta de Catalunya.En el proyecto se ha realizado un trabajo de análisis de las prácticas programadas en las distintas universidades para velar por la calidad de los trabajos fin de grado, actualmente proyectos fin carrera. Se han recopilado diferentes procedimientos de evaluación llevados a cabo en diferentes Universidades que van desde plantillas de verificación para los tribunales de los proyectos a guías de procedimiento completas que verifican elestablecimiento y cumplimiento de hitos intermedios.En esta comunicación se muestra la aplicación de algunas de las prácticas propuestas en el caso real de proyectos fin de carrera en la titulación de Ingeniería Técnica en Diseño Industrial de la Escuela de Ingenierías Industriales. Se pone de manifiesto la utilidad del uso de dichas prácticas frente a enfoques más clásicos o simplistas.

Personalized modeling for drug concentration prediction using Support Vector Machine

Building a personalized model to describe the drug concentration inside the human body for each patient is highly important to the clinical practice and demanding to the modeling tools. Instead of using traditional explicit methods, in this paper we propose a machine learning approach to describe the relation between the drug concentration and patients' features. Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. We focus mainly on the prediction of the drug concentrations as well as the analysis of different features' influence. Models are built based on Support Vector Machine and the prediction results are compared with the traditional analytical models.

Efficiency-based evaluation of aligners for industrial applications

This paper presents a novel efficiencybased evaluation of sentence and word aligners. This assessment is critical in order to make a reliable use in industrial scenarios. The evaluation shows that the resourcesrequired by aligners differ rather broadly. Subsequently, we establish limitation mechanisms on a set of aligners deployed as web services. These results, paired with the quality expected from the aligners, allow providers to choose the most appropriate aligner according to the task at hand.

Student modeling based on fuzzy inference mechanisms

The paper presents a competence-based instructional design system and a way to provide a personalization of navigation in the course content. The navigation aid tool builds on the competence graph and the student model, which includes the elements of uncertainty in the assessment of students. An individualized navigation graph is constructed for each student, suggesting the competences the student is more prepared to study. We use fuzzy set theory for dealing with uncertainty. The marks of the assessment tests are transformed into linguistic terms and used for assigning values to linguistic variables. For each competence, the level of difficulty and the level of knowing its prerequisites are calculated based on the assessment marks. Using these linguistic variables and approximate reasoning (fuzzy IF-THEN rules), a crisp category is assigned to each competence regarding its level of recommendation.

Union activism in an inclusive model of industrial relations : evidence from an Spanish case

In this article we analyze the reasons, within the context of Spanish industrial relations, for trade union members’ active participation in their regional union. The case of Spain is particularly interesting as the unions’ main activity, collective bargaining, is a public good. The text, based on research involving a representative survey of members of a regional branch of the “Workers” Commissions” (Comisiones Obreras) trade union, provides empirical evidence that the union presence in the workplace has a significant influence on members’ propensity for activism. By contrast, the alternative hypothesis based on instrumental reasons appears of little relevance in the Spanish industrial relations context.

Prediction of infant drug exposure through breastfeeding: population PK modeling and simulation of fluoxetine

BACKGROUND: Risks of significant infant drug exposurethrough breastmilk are poorly defined for many drugs, and largescalepopulation data are lacking. We used population pharmacokinetics(PK) modeling to predict fluoxetine exposure levels ofinfants via mother's milk in a simulated population of 1000 motherinfantpairs.METHODS: Using our original data on fluoxetine PK of 25breastfeeding women, a population PK model was developed withNONMEM and parameters, including milk concentrations, wereestimated. An exponential distribution model was used to account forindividual variation. Simulation random and distribution-constrainedassignment of doses, dosing time, feeding intervals and milk volumewas conducted to generate 1000 mother-infant pairs with characteristicssuch as the steady-state serum concentrations (Css) and infantdose relative to the maternal weight-adjusted dose (relative infantdose: RID). Full bioavailability and a conservative point estimate of1-month-old infant CYP2D6 activity to be 20% of the adult value(adjusted by weigth) according to a recent study, were assumed forinfant Css calculations.RESULTS: A linear 2-compartment model was selected as thebest model. Derived parameters, including milk-to-plasma ratios(mean: 0.66; SD: 0.34; range, 0 - 1.1) were consistent with the valuesreported in the literature. The estimated RID was below 10% in >95%of infants. The model predicted median infant-mother Css ratio was0.096 (range 0.035 - 0.25); literature reported mean was 0.07 (range0-0.59). Moreover, the predicted incidence of infant-mother Css ratioof >0.2 was less than 1%.CONCLUSION: Our in silico model prediction is consistent withclinical observations, suggesting that substantial systemic fluoxetineexposure in infants through human milk is rare, but further analysisshould include active metabolites. Our approach may be valid forother drugs. [supported by CIHR and Swiss National Science Foundation(SNSF)]

The challenge of modeling nuclear receptor regulatory networks in mammalian cells.

Nuclear receptors are a major component of signal transduction in animals. They mediate the regulatory activities of many hormones, nutrients and metabolites on the homeostasis and physiology of cells and tissues. It is of high interest to model the corresponding regulatory networks. While molecular and cell biology studies of individual promoters have provided important mechanistic insight, a more complex picture is emerging from genome-wide studies. The regulatory circuitry of nuclear receptor regulated gene expression networks, and their response to cellular signaling, appear highly dynamic, and involve long as well as short range chromatin interactions. We review how progress in understanding the kinetics and regulation of cofactor recruitment, and the development of new genomic methods, provide opportunities but also a major challenge for modeling nuclear receptor mediated regulatory networks.

Aerodynamic drag modeling of alpine skiers performing giant slalom turns.

PURPOSE: Aerodynamic drag plays an important role in performance for athletes practicing sports that involve high-velocity motions. In giant slalom, the skier is continuously changing his/her body posture, and this affects the energy dissipated in aerodynamic drag. It is therefore important to quantify this energy to understand the dynamic behavior of the skier. The aims of this study were to model the aerodynamic drag of alpine skiers in giant slalom simulated conditions and to apply these models in a field experiment to estimate energy dissipated through aerodynamic drag. METHODS: The aerodynamic characteristics of 15 recreational male and female skiers were measured in a wind tunnel while holding nine different skiing-specific postures. The drag and the frontal area were recorded simultaneously for each posture. Four generalized and two individualized models of the drag coefficient were built, using different sets of parameters. These models were subsequently applied in a field study designed to compare the aerodynamic energy losses between a dynamic and a compact skiing technique. RESULTS: The generalized models estimated aerodynamic drag with an accuracy of between 11.00% and 14.28%, and the individualized models estimated aerodynamic drag with an accuracy between 4.52% and 5.30%. The individualized model used for the field study showed that using a dynamic technique led to 10% more aerodynamic drag energy loss than using a compact technique. DISCUSSION: The individualized models were capable of discriminating different techniques performed by advanced skiers and seemed more accurate than the generalized models. The models presented here offer a simple yet accurate method to estimate the aerodynamic drag acting upon alpine skiers while rapidly moving through the range of positions typical to turning technique.

Audit report on America's Agricultural Industrial Heritage Landscape Inc., D/B/A Silos and Smokestacks National Heritage Area, Independent Auditor's Reports, Financial Statements and Supplementary Information, Schedule of Findings and Questioned Costs, December 31, 2004 & 2005

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