Genetic association studies under the population stratification, family pedigree and application to genome-wide association studies

This dissertation has three separate parts: the first part deals with the general pedigree association testing incorporating continuous covariates; the second part deals with the association tests under population stratification using the conditional likelihood tests; the third part deals with the genome-wide association studies based on the real rheumatoid arthritis (RA) disease data sets from Genetic Analysis Workshop 16 (GAW16) problem 1. Many statistical tests are developed to test the linkage and association using either case-control status or phenotype covariates for family data structure, separately. Those univariate analyses might not use all the information coming from the family members in practical studies. On the other hand, the human complex disease do not have a clear inheritance pattern, there might exist the gene interactions or act independently. In part I, the new proposed approach MPDT is focused on how to use both the case control information as well as the phenotype covariates. This approach can be applied to detect multiple marker effects. Based on the two existing popular statistics in family studies for case-control and quantitative traits respectively, the new approach could be used in the simple family structure data set as well as general pedigree structure. The combined statistics are calculated using the two statistics; A permutation procedure is applied for assessing the p-value with adjustment from the Bonferroni for the multiple markers. We use simulation studies to evaluate the type I error rates and the powers of the proposed approach. Our results show that the combined test using both case-control information and phenotype covariates not only has the correct type I error rates but also is more powerful than the other existing methods. For multiple marker interactions, our proposed method is also very powerful. Selective genotyping is an economical strategy in detecting and mapping quantitative trait loci in the genetic dissection of complex disease. When the samples arise from different ethnic groups or an admixture population, all the existing selective genotyping methods may result in spurious association due to different ancestry distributions. The problem can be more serious when the sample size is large, a general requirement to obtain sufficient power to detect modest genetic effects for most complex traits. In part II, I describe a useful strategy in selective genotyping while population stratification is present. Our procedure used a principal component based approach to eliminate any effect of population stratification. The paper evaluates the performance of our procedure using both simulated data from an early study data sets and also the HapMap data sets in a variety of population admixture models generated from empirical data. There are one binary trait and two continuous traits in the rheumatoid arthritis dataset of Problem 1 in the Genetic Analysis Workshop 16 (GAW16): RA status, AntiCCP and IgM. To allow multiple traits, we suggest a set of SNP-level F statistics by the concept of multiple-correlation to measure the genetic association between multiple trait values and SNP-specific genotypic scores and obtain their null distributions. Hereby, we perform 6 genome-wide association analyses using the novel one- and two-stage approaches which are based on single, double and triple traits. Incorporating all these 6 analyses, we successfully validate the SNPs which have been identified to be responsible for rheumatoid arthritis in the literature and detect more disease susceptibility SNPs for follow-up studies in the future. Except for chromosome 13 and 18, each of the others is found to harbour susceptible genetic regions for rheumatoid arthritis or related diseases, i.e., lupus erythematosus. This topic is discussed in part III.

Taking personalized medicine seriously: Biomarker approaches in phase IIb/III studies in major depression and schizophrenia

The success rate in the development of psychopharmacological compounds is insufficient. Two main reasons for failure have been frequently identified: 1) treating the wrong patients and 2) using the wrong dose. This is potentially based on the known heterogeneity among patients, both on a syndromal and a biological level. A focus on personalized medicine through better characterization with biomarkers has been successful in other therapeutic areas. Nevertheless, obstacles toward this goal that exist are 1) the perception of a lack of validation, 2) the perception of an expensive and complicated enterprise, and 3) the perception of regulatory hurdles. The authors tackle these concerns and focus on the utilization of biomarkers as predictive markers for treatment outcome. The authors primarily cover examples from the areas of major depression and schizophrenia. Methodologies covered include salivary and plasma collection of neuroendocrine, metabolic, and inflammatory markers, which identified subgroups of patients in the Netherlands Study of Depression and Anxiety. A battery of vegetative markers, including sleep-electroencephalography parameters, heart rate variability, and bedside functional tests, can be utilized to characterize the activity of a functional system that is related to treatment refractoriness in depression (e.g., the renin-angiotensin-aldosterone system). Actigraphy and skin conductance can be utilized to classify patients with schizophrenia and provide objective readouts for vegetative activation as a functional marker of target engagement. Genetic markers, related to folate metabolism, or folate itself, has prognostic value for the treatment response in patients with schizophrenia. Already, several biomarkers are routinely collected in standard clinical trials (e.g., blood pressure and plasma electrolytes), and appear to be differentiating factors for treatment outcome. Given the availability of a wide variety of markers, the further development and integration of such markers into clinical research is both required and feasible in order to meet the benefit of personalized medicine. This article is based on proceedings from the "Taking Personalized Medicine Seriously-Biomarker Approaches in Phase IIb/III Studies in Major Depression and Schizophrenia" session, which was held during the 10th Annual Scientific Meeting of the International Society for Clinical Trials Meeting (ISCTM) in Washington, DC, February 18 to 20, 2014.

Motivational profiles of sport event volunteers.

Aim of the study Due to the valuable contribution made by volunteers to sporting events, a better understanding of volunteers’ motivation is imperative for event managers in order to develop effective volunteer re-cruitment and retention strategies. The adoption of working conditions and task domains to the mo-tives and needs of volunteers is one of the key challenges in volunteer management. Conversely, an ignorance of the motives and needs of volunteers could negatively affect their performance and attitude, which will have negative consequences for the execution of events (Strigas & Jackson, 2003). In general, the motives of volunteers are located on a continuum between selflessness (e.g. helping others), and self-interest (e.g. pursuing one’s own interests). Furthermore, it should take into account that volunteers may be motivated by more than one need or goal, and therefore, configure different bundles of motives, resulting in heterogeneous types of motives for voluntary engagement (Dolnicar & Randle, 2007). Despite the extensive number of studies on the motives of sport event volunteers, only few studies focus on the analysis of individual motive profiles concerning volun-teering. Accordingly, we will take a closer look at the following questions: To what extent do volun-teers at sporting events differ in the motives of their engagement, and how can the volunteers be ade-quately classified? Theoretical Background According to the functional approach, relevant subjective motives are related to the outcomes and consequences that volunteering is supposed to lead to and to produce. This means, individuals’ mo-tives determine which incentives are anticipated in return for volunteering (e.g. increase in social contacts), and are important for engaging in volunteering, e.g. the choice between different oppor-tunities for voluntary activity, or different tasks (Stukas et al., 2009). Additionally, inter-individual differences of motive structures as well as matching motives in the reflections of voluntary activities will be considered by using a person-oriented approach. In the person-oriented approach, it is not the specific variables that are made the entities of investigation, but rather persons with a certain combination of characteristic features (Bergmann et al., 2003). Person-orientation in the field of sports event volunteers, it is therefore essential to implement an orientation towards people as a unit of analysis. Accordingly, individual motive profiles become the object of investigation. The individ-ual motive profiles permit a glimpse of intra-individual differences in the evaluation of different motive areas, and thus represent the real subjective perspective. Hence, a person will compare the importance of individual motives for his behaviour primarily in relation to other motives (e.g. social contacts are more important to me than material incentives), and make fewer comparisons with the assessments of other people. Methodology, research design and data analysis The motives of sports event volunteers were analysed in the context of the European Athletics Championships 2014 in Zürich. After data cleaning, the study sample contained a total of 1,169 volunteers, surveyed by an online questionnaire. The VMS-ISA scale developed by Bang and Chel-ladurai (2009) was used and replicated successfully by a confirmatory factor analysis. Accordingly, all seven factors of the scale were included in the subsequent cluster analysis to determine typical motive profiles of volunteers. Before proceeding with the cluster analysis, an intra-individual stand-ardization procedure (according to Spiel, 1998) was applied to take advantage of the intra-individual relationships between the motives of the volunteers. Intra-individual standardization means that every value of each motive dimension was related to the average individual level of ex-pectations. In the final step, motive profiles were determined using a hierarchic cluster analysis based on Ward’s method with squared Euclidean distances. Results, discussion and implications The results reveal that motivational processes differ among sports event volunteers, and that volunteers sometimes combine contradictory bundles of motives. In our study, four different volunteer motive profiles were identified and described by their positive levels on the individual motive dimension: the community supporters, the material incentive seekers, the social networkers, and the career and personal growth pursuers. To describe the four identified motive profiles in more detail and to externally validate them, the clusters were analysed in relation to socio-economic, sport-related, and voluntary work characteristics. This motive-based typology of sports event volunteers can provide valuable guidance for event managers in order to create distinctive and designable working conditions and tasks at sporting events that should, in relation to a person-oriented approach, be tailored to a wide range of individ-ual prerequisites. Furthermore, specific recruitment procedures and appropriate communication measures can be defined in order to approach certain groups of potential volunteers more effectively. References Bang, H., & Chelladurai, P. (2009). Development and validation of the volunteer motivations scale for international sporting events (VMS-ISE). International Journal Sport Management and Market-ing, 6, 332-350. Bergmann, L. R., Magnusson, D., & El-Khouri, B. M. (2003). Studying individual development in an interindividual context. Mahwah, NJ: Erlbaum. Dolnicar, S., & Randle, M. (2007). What motivates which volunteers? Psychographic heterogeneity among volunteers in Australia. Voluntas, 18, 135-155. Spiel, C. (1998). Four methodological approaches to the study of stability and change in develop-ment. Methods of Psychological Research Online, 3, 8-22. Stukas, A. A., Worth, K. A., Clary, E. G., & Snyder, M. (2009). The matching of motivations to affordances in the volunteer environment: an index for assessing the impact of multiple matches on volunteer outcomes. Nonprofit and Voluntary Sector Quarterly, 38, 5-28.

WOCAT - World Overview of Conservation Approaches and Technologies - Preliminary results from Eastern and Southern Africa

The World Overview of Conservation Approaches and Technologies (WOCAT) is a program of the World Association of Soil and Water Conservation (WASWC), organized as a consortium of several international institutions. The overall goal of WOCAT is to contribute to sustainable utilization of soil and water. WOCAT collects and analyzes information on soil and water conservation (SWC) technologies and approaches world-wide, and presents the collected information in computer databases and decision support systems, and in the form of handbooks, reports and maps readily accessible to SWC specialists and policy-makers world-wide. WOCAT has prepared a framework for the evaluation of soil and water conservation and has started data collection. The paper presents preliminary results with promising SWC technologies and approaches used in Eastern and Southern Africa. The first finding is that hardly any promising SWC activities could be found on common grazing lands. Analysis of the cropland shows some of the bio-physical and socioeconomic conditions under which certain SWC technologies and approaches are used, including land use types, climatic zones and land tenure, and looks at issues such as participation and costs. Furthermore, classification criteria for SWC technologies and approaches are discussed.

The information bottleneck method for genome-wide association studies

In population studies, most current methods focus on identifying one outcome-related SNP at a time by testing for differences of genotype frequencies between disease and healthy groups or among different population groups. However, testing a great number of SNPs simultaneously has a problem of multiple testing and will give false-positive results. Although, this problem can be effectively dealt with through several approaches such as Bonferroni correction, permutation testing and false discovery rates, patterns of the joint effects by several genes, each with weak effect, might not be able to be determined. With the availability of high-throughput genotyping technology, searching for multiple scattered SNPs over the whole genome and modeling their joint effect on the target variable has become possible. Exhaustive search of all SNP subsets is computationally infeasible for millions of SNPs in a genome-wide study. Several effective feature selection methods combined with classification functions have been proposed to search for an optimal SNP subset among big data sets where the number of feature SNPs far exceeds the number of observations. ^ In this study, we take two steps to achieve the goal. First we selected 1000 SNPs through an effective filter method and then we performed a feature selection wrapped around a classifier to identify an optimal SNP subset for predicting disease. And also we developed a novel classification method-sequential information bottleneck method wrapped inside different search algorithms to identify an optimal subset of SNPs for classifying the outcome variable. This new method was compared with the classical linear discriminant analysis in terms of classification performance. Finally, we performed chi-square test to look at the relationship between each SNP and disease from another point of view. ^ In general, our results show that filtering features using harmononic mean of sensitivity and specificity(HMSS) through linear discriminant analysis (LDA) is better than using LDA training accuracy or mutual information in our study. Our results also demonstrate that exhaustive search of a small subset with one SNP, two SNPs or 3 SNP subset based on best 100 composite 2-SNPs can find an optimal subset and further inclusion of more SNPs through heuristic algorithm doesn't always increase the performance of SNP subsets. Although sequential forward floating selection can be applied to prevent from the nesting effect of forward selection, it does not always out-perform the latter due to overfitting from observing more complex subset states. ^ Our results also indicate that HMSS as a criterion to evaluate the classification ability of a function can be used in imbalanced data without modifying the original dataset as against classification accuracy. Our four studies suggest that Sequential Information Bottleneck(sIB), a new unsupervised technique, can be adopted to predict the outcome and its ability to detect the target status is superior to the traditional LDA in the study. ^ From our results we can see that the best test probability-HMSS for predicting CVD, stroke,CAD and psoriasis through sIB is 0.59406, 0.641815, 0.645315 and 0.678658, respectively. In terms of group prediction accuracy, the highest test accuracy of sIB for diagnosing a normal status among controls can reach 0.708999, 0.863216, 0.639918 and 0.850275 respectively in the four studies if the test accuracy among cases is required to be not less than 0.4. On the other hand, the highest test accuracy of sIB for diagnosing a disease among cases can reach 0.748644, 0.789916, 0.705701 and 0.749436 respectively in the four studies if the test accuracy among controls is required to be at least 0.4. ^ A further genome-wide association study through Chi square test shows that there are no significant SNPs detected at the cut-off level 9.09451E-08 in the Framingham heart study of CVD. Study results in WTCCC can only detect two significant SNPs that are associated with CAD. In the genome-wide study of psoriasis most of top 20 SNP markers with impressive classification accuracy are also significantly associated with the disease through chi-square test at the cut-off value 1.11E-07. ^ Although our classification methods can achieve high accuracy in the study, complete descriptions of those classification results(95% confidence interval or statistical test of differences) require more cost-effective methods or efficient computing system, both of which can't be accomplished currently in our genome-wide study. We should also note that the purpose of this study is to identify subsets of SNPs with high prediction ability and those SNPs with good discriminant power are not necessary to be causal markers for the disease.^

Identification of diabetic retinopathy genes through a genome-wide association study among Mexican-Americans from Starr County, Texas

To identify genetic susceptibility loci for severe diabetic retinopathy, 286 Mexican-Americans with type 2 diabetes from Starr County, Texas completed detailed physical and ophthalmologic examinations including fundus photography for diabetic retinopathy grading. 103 individuals with moderate-to-severe non-proliferative diabetic retinopathy or proliferative diabetic retinopathy were defined as cases for this study. DNA samples extracted from study subjects were genotyped using the Affymetrix GeneChip® Human Mapping 100K Set, which includes 116,204 single nucleotide polymorphisms (SNPs) across the whole genome. Single-marker allelic tests and 2- to 8-SNP sliding-window Haplotype Trend Regression implemented in HelixTreeTM were first performed with these direct genotypes to identify genes/regions contributing to the risk of severe diabetic retinopathy. An additional 1,885,781 HapMap Phase II SNPs were imputed from the direct genotypes to expand the genomic coverage for a more detailed exploration of genetic susceptibility to diabetic retinopathy. The average estimated allelic dosage and imputed genotypes with the highest posterior probabilities were subsequently analyzed for associations using logistic regression and Fisher's Exact allelic tests, respectively. To move beyond these SNP-based approaches, 104,572 directly genotyped and 333,375 well-imputed SNPs were used to construct genetic distance matrices based on 262 retinopathy candidate genes and their 112 related biological pathways. Multivariate distance matrix regression was then used to test hypotheses with genes and pathways as the units of inference in the context of susceptibility to diabetic retinopathy. This study provides a framework for genome-wide association analyses, and implicated several genes involved in the regulation of oxidative stress, inflammatory processes, histidine metabolism, and pancreatic cancer pathways associated with severe diabetic retinopathy. Many of these loci have not previously been implicated in either diabetic retinopathy or diabetes. In summary, CDC73, IL12RB2, and SULF1 had the best evidence as candidates to influence diabetic retinopathy, possibly through novel biological mechanisms related to VEGF-mediated signaling pathway or inflammatory processes. While this study uncovered some genes for diabetic retinopathy, a comprehensive picture of the genetic architecture of diabetic retinopathy has not yet been achieved. Once fully understood, the genetics and biology of diabetic retinopathy will contribute to better strategies for diagnosis, treatment and prevention of this disease.^

Pathway analysis of genome-wide association study data in primary biliary cirrhosisa

Genome-wide association studies (GWAS) have successfully identified several genetic loci associated with inherited predisposition to primary biliary cirrhosis (PBC), the most common autoimmune disease of the liver. Pathway-based tests constitute a novel paradigm for GWAS analysis. By evaluating genetic variation across a biological pathway (gene set), these tests have the potential to determine the collective impact of variants with subtle effects that are individually too weak to be detected in traditional single variant GWAS analysis. To identify biological pathways associated with the risk of development of PBC, GWAS of PBC from Italy (449 cases and 940 controls) and Canada (530 cases and 398 controls) were independently analyzed. The linear combination test (LCT), a recently developed pathway-level statistical method was used for this analysis. For additional validation, pathways that were replicated at the P <0.05 level of significance in both GWAS on LCT analysis were also tested for association with PBC in each dataset using two complementary GWAS pathway approaches. The complementary approaches included a modification of the gene set enrichment analysis algorithm (i-GSEA4GWAS) and Fisher's exact test for pathway enrichment ratios. Twenty-five pathways were associated with PBC risk on LCT analysis in the Italian dataset at P<0.05, of which eight had an FDR<0.25. The top pathway in the Italian dataset was the TNF/stress related signaling pathway (p=7.38×10 -4, FDR=0.18). Twenty-six pathways were associated with PBC at the P<0.05 level using the LCT in the Canadian dataset with the regulation and function of ChREBP in liver pathway (p=5.68×10-4, FDR=0.285) emerging as the most significant pathway. Two pathways, phosphatidylinositol signaling system (Italian: p=0.016, FDR=0.436; Canadian: p=0.034, FDR=0.693) and hedgehog signaling (Italian: p=0.044, FDR=0.636; Canadian: p=0.041, FDR=0.693), were replicated at LCT P<0.05 in both datasets. Statistically significant association of both pathways with PBC genetic susceptibility was confirmed in the Italian dataset on i-GSEA4GWAS. Results for the phosphatidylinositol signaling system were also significant in both datasets on applying Fisher's exact test for pathway enrichment ratios. This study identified a combination of known and novel pathway-level associations with PBC risk. If functionally validated, the findings may yield fresh insights into the etiology of this complex autoimmune disease with possible preventive and therapeutic application.^

Gene-gene interaction and gene-pathway analysis of genome-wide association for schizophrenia

Schizophrenia (SZ) is a complex disorder with high heritability and variable phenotypes that has limited success in finding causal genes associated with the disease development. Pathway-based analysis is an effective approach in investigating the molecular mechanism of susceptible genes associated with complex diseases. The etiology of complex diseases could be a network of genetic factors and within the genes, interaction may occur. In this work we argue that some genes might be of small effect that by itself are neither sufficient nor necessary to cause the disease however, their effect may induce slight changes to the gene expression or affect the protein function, therefore, analyzing the gene-gene interaction mechanism within the disease pathway would play crucial role in dissecting the genetic architecture of complex diseases, making the pathway-based analysis a complementary approach to GWAS technique. ^ In this study, we implemented three novel linkage disequilibrium based statistics, the linear combination, the quadratic, and the decorrelation test statistics, to investigate the interaction between linked and unlinked genes in two independent case-control GWAS datasets for SZ including participants of European (EA) and African (AA) ancestries. The EA population included 1,173 cases and 1,378 controls with 729,454 genotyped SNPs, while the AA population included 219 cases and 288 controls with 845,814 genotyped SNPs. We identified 17,186 interacting gene-sets at significant level in EA dataset, and 12,691 gene-sets in AA dataset using the gene-gene interaction method. We also identified 18,846 genes in EA dataset and 19,431 genes in AA dataset that were in the disease pathways. However, few genes were reported of significant association to SZ. ^ Our research determined the pathways characteristics for schizophrenia through the gene-gene interaction and gene-pathway based approaches. Our findings suggest insightful inferences of our methods in studying the molecular mechanisms of common complex diseases.^

Territorial approaches for rural development in Latin America : a case study in Chile

Una reciente transición en el campo del desarrollo rural es el movimiento desde un enfoque reducido del sector agrícola hasta uno que adopta una visión territorial más amplia. Este pasaje intenta interpretar las interacciones entre los mundos urbano y rural de una manera más comprensiva. Esta perspectiva teórica relativamente nueva interesa particularmente a los académicos y los políticos en los países latinoamericanos donde, a partir de la mitad de los años noventa, el concepto de una nueva ruralidad se ha visto como la fuente de un nuevo enfoque para el desarrollo rural. Por lo tanto, el propósito teórico de esta investigación es explicitar los indicadores analíticos del nuevo enfoque de la ruralidad en América Latina e identificar las diferencias entre los acercamientos sectoriales y territoriales, considerando los aspectos socio-económicos, institucionales y medioambientales involucrados. La transición del enfoque sectorial a uno territorial significa también, desde un punto de vista operativo, el reconocimiento de la existencia de áreas homogéneas a partir de las cuales pueden proponerse estrategias de desarrollo rural. El propósito operativo de esta investigación consiste en proponer una metodología para identificar estas áreas con una aplicación a la Región del Maule en Chile. La conclusión subraya algunos elementos críticos que se deben considerar en la definición de estrategias del desarrollo rural territorial.

Análisis de la institucionalidad asociada a los procesos de innovación tecnológica en el sector hortícola del Gran La Plata

La Extensión Rural, como mecanismo para propender al desarrollo rural en la Argentina, ha sido la herramienta por excelencia utilizada por los Estados para lograr objetivos institucionales vinculados a las políticas dominantes. El presente trabajo se propone analizar la institucionalidad asociada a la Extensión Rural y Asistencia Técnica en el sector hortícola del Gran La Plata luego de la crisis del 2001, como instrumento de apoyo al desarrollo rural. Para ello identifica a los actores del sector público y de la sociedad civil vinculados al proceso de innovación tecnológica que participan en la construcción de una nueva institucionalidad y los enfoques paradigmáticos emergentes, presentes en la agricultura familiar de la región. Se concluye que los cambios institucionales que se están operando, como resultado de una nueva visión de la institucionalidad que se está construyendo, están dando lugar a estrategias de intervención novedosas para la región, siendo cada vez más frecuentes las acciones que operan a favor de la agricultura familiar

Análisis de la institucionalidad asociada a los procesos de innovación tecnológica en el sector hortícola del Gran La Plata

La Extensión Rural, como mecanismo para propender al desarrollo rural en la Argentina, ha sido la herramienta por excelencia utilizada por los Estados para lograr objetivos institucionales vinculados a las políticas dominantes. El presente trabajo se propone analizar la institucionalidad asociada a la Extensión Rural y Asistencia Técnica en el sector hortícola del Gran La Plata luego de la crisis del 2001, como instrumento de apoyo al desarrollo rural. Para ello identifica a los actores del sector público y de la sociedad civil vinculados al proceso de innovación tecnológica que participan en la construcción de una nueva institucionalidad y los enfoques paradigmáticos emergentes, presentes en la agricultura familiar de la región. Se concluye que los cambios institucionales que se están operando, como resultado de una nueva visión de la institucionalidad que se está construyendo, están dando lugar a estrategias de intervención novedosas para la región, siendo cada vez más frecuentes las acciones que operan a favor de la agricultura familiar

Análisis de la institucionalidad asociada a los procesos de innovación tecnológica en el sector hortícola del Gran La Plata

La Extensión Rural, como mecanismo para propender al desarrollo rural en la Argentina, ha sido la herramienta por excelencia utilizada por los Estados para lograr objetivos institucionales vinculados a las políticas dominantes. El presente trabajo se propone analizar la institucionalidad asociada a la Extensión Rural y Asistencia Técnica en el sector hortícola del Gran La Plata luego de la crisis del 2001, como instrumento de apoyo al desarrollo rural. Para ello identifica a los actores del sector público y de la sociedad civil vinculados al proceso de innovación tecnológica que participan en la construcción de una nueva institucionalidad y los enfoques paradigmáticos emergentes, presentes en la agricultura familiar de la región. Se concluye que los cambios institucionales que se están operando, como resultado de una nueva visión de la institucionalidad que se está construyendo, están dando lugar a estrategias de intervención novedosas para la región, siendo cada vez más frecuentes las acciones que operan a favor de la agricultura familiar

ERP Software Selection Processes: A Case Study in the Metal Transformation Sector

When a firm decides to implement ERP softwares, the resulting consequences can pervade all levels, includ- ing organization, process, control and available information. Therefore, the first decision to be made is which ERP solution must be adopted from a wide range of offers and vendors. To this end, this paper describes a methodology based on multi-criteria factors that directly affects the process to help managers make this de- cision. This methodology has been applied to a medium-size company in the Spanish metal transformation sector which is interested in updating its IT capabilities in order to obtain greater control of and better infor- mation about business, thus achieving a competitive advantage. The paper proposes a decision matrix which takes into account all critical factors in ERP selection.

Evaluación de competencias en programas de formación en el sector rural : el caso de la maestría tecnológica para prestadores de servicios profesionales (PSP) en México

El objetivo de la presente investigación doctoral es proponer una metodología para evaluar las competencias en programas de formación en el sector rural mexicano. Para ello hemos realizado una exhausta revisión documental a nivel internacional sobre el concepto de competencia, sus orígenes y su evolución, para poder diseñar la metodología de su evaluación, así como el identificar los diferentes enfoques, herramientas y técnicas utilizadas actualmente para la evaluación de las competencias. Una vez comprendido el concepto de competencia, haber observado que existen saberes implícitos en ella, además de haber identificado las competencias necesarias por parte de los actores sociales presentes en el medio rural mexicano para el logro de un desarrollo rural integral dentro de sus territorios, y haberlos integrado en el diseño de la metodología, hemos realizado una propuesta metodológica considerando los instrumentos disponibles en México y enmarcados en la normativa legal vigente, que pudieran aportar evidencias de desempeño de un sujeto. Además como parte de la metodología se ha diseñado y validado un cuestionario psicométrico para poder evaluar las competencias personales de los sujetos presentes en el medio rural mexicano. La aplicación empírica de la metodología propuesta fue realizada a un estudio de caso en México, particularmente a Prestadores de Servicios Profesionales (PSP) del medio rural, estudiantes de una maestría tecnológica diseñada bajo un enfoque de competencias por el Colegio de Postgraduados, Institución de enseñanza, investigación y servicio en Ciencias Agrícolas. Los resultados evidencian que la propuesta metodológica es significativa para poder evaluar las competencias en el sector rural mexicano. Abstract The objective of this PhD thesis is to propose a methodology to assess competences in training programs in rural Mexico. We therefore performed an exhausted international literature review on the concept of competence, its origins and evolution, in order to design their evaluation methodology and also identified the different approaches, tools and techniques currently used for the assessment of competences. Once we understand the concept of competence, have noticed that there are implicit knowledge in it, and having identified the competences needed by social actors in rural Mexico, for the achievement of a integrated rural development within their territories, and integrated them into the design of the methodology, we have made a methodology considering the tools available in Mexico and framed in the current legislation, which could provide evidence of performance of a subject. Also as part of the methodology we designed and validated a psychometric questionnaire to assess behavioral competences of the individuals present in rural Mexico. The empirical application of the proposed methodology was performed at a case study in Mexico, particularly to providers of farming professionals services (PSP), students from a technological master designed under a competence approach by the Colegio de Postgraduados, an Institution of teaching, research and service in Agricultural Sciences. The results show that the proposed methodology is meaningful to assess competences in rural Mexico.

A comparative analysis of road financing approaches in Europe and the United States

• The viability of the present system of road funding has in recent years been widely questioned, for it has proved insufficient to support spending programs at their current levels. • Some transfers from the general fund have been needed since 2008 to keep the HTF solvent. • Fuel taxes, the primary source for funding roads in the US, have not kept pace with inflation for years. • A wide variety of measures to increase revenue has been presented: raising fuel taxes, extending toll highways, implementing a VMT fee, etc.