Methodologies to measure and to manage the decarbonisation of road transport: the case of Spain

El sector del transporte por carretera es uno de los principales contribuyentes de consumo de combustible y emisiones de España. Por lo tanto, la evaluación de los impactos ambientales del tráfico rodado es esencial para los programas de mitigación del cambio climático y la eficiencia energética. Sin embargo, uno de los retos en la planificación del transporte y el diseño de políticas consiste en la aplicación de metodologías de evaluación de emisiones consistentes, el diseño de estrategias y la evaluación de su eficacia. Las metodologías existentes de evaluación de las emisiones del transporte por carretera, utilizan diferentes niveles de análisis y períodos. Sin embargo, estos análisis son puntuales y no existe una continuidad en el análisis de diferentes estrategias o políticas. Esta tesis doctoral proporciona conocimientos y herramientas para el análisis de las políticas destinadas a reducir las emisiones de tráfico, tomando España como caso de estudio. La investigación se estructura en dos partes: i) el desarrollo y aplicación de metodologías para el análisis de factores y políticas que contribuyen en la evolución de las emisiones GEI del transporte por carretera en España; desde una perspectiva nacional; y ii) el desarrollo y aplicación de un marco metodológico para estimar las emisiones del tráfico interurbano y de evaluar estrategias centradas en la operación del tráfico y en la infraestructura. En resumen, esta tesis demuestra la idoneidad de utilizar diferentes herramientas para analizar las emisiones de tráfico desde diferentes puntos de vista. Desde el diseño de políticas de mitigación y eficiencia energética a nivel nacional, a estrategias centradas en la operación del tráfico interurbano y la infraestructura. Road transport is one of the major contributors to fuel consumption and emissions in Spain. Consequently, assessing the environmental impacts of road traffic is essential for climate change mitigation and energy efficiency programs. However, one of the key challenges of policy makers and transport planners consists of implementing consistent assessment emissions methodologies, applying mitigation strategies, and knowing their effectiveness. Current state-of-the-art emissions assessment methodologies estimate emissions from different levels and periods, using different approaches. Nevertheless, these studies are timely and they usually take different methodologies for analysing different strategies or policies, regardless of the assessment as a whole. This doctoral thesis provides knowledge and methodologies for analysing policies designed to reduce road traffic emissions, using the case study of Spain. The research procedure consists of two main scopes: i) the development and application of methodologies for analysing key factors and policies driving the GHG emissions of road transport in Spain; from a national perspective; and ii) the development and application of a road traffic emissions model for assessing operational and infrastructure strategies of the interurban road network at segment level. In summary, this thesis demonstrates the appropriateness to use different tools to analyse road traffic emissions at different levels: from appropriate nationwide mitigation and energy efficiency policies, to strategies focused on the operation of interurban traffic and infrastructure.

A CO2-saving-based methodology to measure the impact of the SUMP in European Cities: Application to the City of Burgos

Urban mobility in Europe is always a responsibility of the municipalities which propose measures to reduce CO2 emissions in terms of mobility aimed at reducing individual private transport (car). The European Commission's Action Plan on Urban Mobility calls for an increase in the take-up of Sustainable Urban Mobility Plans in Europe. SUMPs aim to create a sustainable urban transport system. Europe has got some long term initiatives and has been using some evaluation procedures, many of them through European projects. Nevertheless, the weak point with the SUMPs in Spain, has been the lack of concern about the evaluation and the effectiveness of the measures implemented in a SUMP. For this reason, it is difficult to know exactly whether or not the SUMPs have positively influenced in the modal split of the cities, and its contribution to reduce CO2 levels. The case of the City of Burgos is a very illustrative example as it developed a CiViTAS project during the years 2005-2009, with a total investment of 6M?. The results have been considered as ?very successful? even at European level. The modal split has changed considerably for better, The cost-effectiveness ratio of the SUMP in the city can be measured with the CO2 ton saved, specifically 36 ? per CO2 ton saved, which is fully satisfactory and in line with calculations from other European researchers. Additionally, the authors propose a single formula to measure the effectiveness of the activities developed under the umbrella of a SUMP.

Designing new cereal cultivars as an adaptation measure using crop model ensembles

To date, crop models have been little used for characterising the types of cultivars suited to a changed climate, though simulations of altered management (e.g. sowing) are often reported. However, in neither case are model uncertainties evaluated at the same time.

Relevance of Higher Education. How to measure it? The case of masters of engineering in Peru

Existing evaluation models for higher education have, mainly, accreditation purposes, and evaluate the efficiency of training programs, that is to say, the degree of suitability between the educational results and the objectives of the program. However, it is not guaranteed that those objectives adequate to the needs and real interests of students and stakeholders, that is to say, they do not assess the relevance of the programs, a very important aspect in developing countries. From the review of experiences, this paper proposes a model for evaluating the relevance of engineering masters program, and applies it to the case of a master?s degree at the University of Piura, Peru. We conclude that the proposed model is applicable to other masters program, offers an objective way for determining is a training program keep being relevant, and identifies improvement opportunities

The optimal measure of allelic association

Allelic association between pairs of loci is derived in terms of the association probability ρ as a function of recombination θ, effective population size N, linear systematic pressure v, and time t, predicting both ρrt, the decrease of association from founders and ρct, the increase by genetic drift, with ρt = ρrt + ρct. These results conform to the Malecot equation, with time replaced by distance on the genetic map, or on the physical map if recombination in the region is uniform. Earlier evidence suggested that ρ is less sensitive to variations in marker allele frequencies than alternative metrics for which there is no probability theory. This robustness is confirmed for six alternatives in eight samples. In none of these 48 tests was the residual variance as small as for ρ. Overall, efficiency was less than 80% for all alternatives, and less than 30% for two of them. Efficiency of alternatives did not increase when information was estimated simultaneously. The swept radius within which substantial values of ρ are conserved lies between 385 and 893 kb, but deviation of parameters between measures is enormously significant. The large effort now being devoted to allelic association has little value unless the ρ metric with the strongest theoretical basis and least sensitivity to marker allele frequencies is used for mapping of marker association and localization of disease loci.

A complexity measure for selective matching of signals by the brain.

We have previously derived a theoretical measure of neural complexity (CN) in an attempt to characterize functional connectivity in the brain. CN measures the amount and heterogeneity of statistical correlations within a neural system in terms of the mutual information between subsets of its units. CN was initially used to characterize the functional connectivity of a neural system isolated from the environment. In the present paper, we introduce a related statistical measure, matching complexity (CM), which reflects the change in CN that occurs after a neural system receives signals from the environment. CM measures how well the ensemble of intrinsic correlations within a neural system fits the statistical structure of the sensory input. We show that CM is low when the intrinsic connectivity of a simulated cortical area is randomly organized. Conversely, CM is high when the intrinsic connectivity is modified so as to differentially amplify those intrinsic correlations that happen to be enhanced by sensory input. When the input is represented by an individual stimulus, a positive value of CM indicates that the limited mutual information between sensory sheets sampling the stimulus and the rest of the brain triggers a large increase in the mutual information between many functionally specialized subsets within the brain. In this way, a complex brain can deal with context and go "beyond the information given."

The deferred imitation task as a nonverbal measure of declarative memory.

We tested amnesic patients, patients with frontal lobe lesions, and control subjects with the deferred imitation task, a nonverbal test used to demonstrate memory abilities in human infants. On day 1, subjects were given sets of objects to obtain a baseline measure of their spontaneous performance of target actions. Then different event sequences were modeled with the object sets. On day 2, the objects were given to the subjects again, first without any instructions to imitate the sequences, and then with explicit instructions to imitate the actions exactly as they had been modeled. Control subjects and frontal lobe patients reproduced the events under both uninstructed and instructed conditions. In contrast, performance by the amnesic patients did not significantly differ from that of a second control group who had the same opportunities to handle the objects but were not shown the modeled actions. These findings suggest that deferred imitation is dependent on the brain structures essential for declarative memory that are damaged in amnesia, and they support the view that infants who imitate actions after long delays have an early capacity for long-term declarative memory.

Analytical method to measure bending deformations in prismatic optical films

The aim of this work is to provide an analytical method based on experimental measurements in order to obtain the prismatic film deformation for different curvatures of Hollow Cylindrical Prismatic Light Guides (CPLG). To conform cylindrical guides is necessary bend the film to guide the light, changes induced by curving the film give rise to deformation shifts. Light losses affected by deformation has been experimentally evaluated and numerically analyzed. The effect of deformation in prism angle is specially increased for CPLG of curvatures higher than 20 m-1. An experimental method for accurate transmittance measurements related to bending is presented.

A new modularity measure for Fuzzy Community detection problems based on overlap and grouping functions

One of the main challenges of fuzzy community detection problems is to be able to measure the quality of a fuzzy partition. In this paper, we present an alternative way of measuring the quality of a fuzzy community detection output based on n-dimensional grouping and overlap functions. Moreover, the proposed modularity measure generalizes the classical Girvan–Newman (GN) modularity for crisp community detection problems and also for crisp overlapping community detection problems. Therefore, it can be used to compare partitions of different nature (i.e. those composed of classical, overlapping and fuzzy communities). Particularly, as is usually done with the GN modularity, the proposed measure may be used to identify the optimal number of communities to be obtained by any network clustering algorithm in a given network. We illustrate this usage by adapting in this way a well-known algorithm for fuzzy community detection problems, extending it to also deal with overlapping community detection problems and produce a ranking of the overlapping nodes. Some computational experiments show the feasibility of the proposed approach to modularity measures through n-dimensional overlap and grouping functions.

Comprehensive Validation Of A Measure Of Student School Engagement: A Pilot Study Of Middle School Students

Although it may sound reasonable that American education continues to be more effective at sending high school students to college, in a study conducted in 2009, The Council of the Great City Schools states that "slightly more than half of entering ninth grade students arrive performing below grade level in reading and math, while one in five entering ninth grade students is more than two years behind grade level...[and] 25% received support in the form of remedial literacy instruction or interventions" (Council of the Great City Schools, 2009). Students are distracted with technology (Lei & Zhao, 2005), family (Xu & Corno, 2003), medical illnesses (Nielson, 2009), learning disabilities and perhaps the most detrimental to academic success, the very lack of interest in school (Ruch, 1963). In a Johns Hopkins research study, Building a Graduation Nation - Colorado (Balfanz, 2008), warning signs were apparent years before the student dropped out of high school. The ninth grade was often referenced as a critical point that indicated success or failure to graduate high school. The research conducted by Johns Hopkins illustrates the problem: students who become disengaged from school have a much greater chance of dropping out of high school and not graduating. The first purpose of this study was to compare different measurement models of the Student School Engagement (SSE) using Factor Analysis to verify model fit with student engagement. The second purpose was to determine the extent to which the SSE instrument measures student school engagement by investigating convergent validity (via the SSE and Appleton, Christenson, Kim and Reschly's instrument and Fredricks, Blumenfeld, Friedel and Paris's instrument), discriminant validity (via Huebner's Student Life Satisfaction Survey) and criterion-related validity (via the sub-latent variables of Aspirations, Belonging and Productivity and student outcome measures such as achievement, attendance and discipline). Discriminant validity was established between the SSE and the Appleton, Christenson, Kim and Reschly's model and Fredricks, Blumenfeld, Friedel and Paris's (2005) Student Engagement Instruments (SEI). When confirming discriminant validity, the SSE's correlations were weak and statistically not significant, thus establishing discriminant validity with the SLSS. Criterion-related validity was established through structural equation modeling when the SSE was found to be a significant predictor of student outcome measures when both risk score and CSAP scores were used. The third purpose of this study was to assess the factorial invariance of the SSE instrument across gender to ensure the instrument is measuring the intended construct across different groups. Conclusively, configural, weak and metric invariances were established for the SSE as a non-significant change in chi-square indicating that all parameters including the error variances were invariant across groups of gender. Engagement is not a clearly defined psychological construct; it requires more research in order to fully comprehend its complexity. Hopefully, with parental and teacher involvement and a sense of community, student engagement can be nurtured to result in a meaningful attachment to school and academic success.

Development of a psychological assessment battery to measure client beliefs about the effectiveness of psychotherapy

The author attempted to develop a brief scale to measure clients' beliefs about the effectiveness of psychotherapy. The study is an early pilot study to determine if the scale can predict therapy outcomes. While the scale did differ significantly between clients who were active in therapy and those who were not, higher scores on the instrument were not indicative of greater involvement. Possibilities for future research to refine the instrument are discussed.

Development of the DORI-TBI: An Investigation to Develop a New Screening Measure to Determine Consultation with a School-Based Brain Injury Resource Team

Brain injury is the leading cause of disability and death in children in the United States. Student re-entry into the school setting following a traumatic brain injury is crucial to student success. Multidisciplinary teams within the school district comprised of individuals with expertise in brain injury are ideal in implementing student specific treatment plans given their specialized training and wide range of expertise addressing student needs. Therefore, the purpose of this study is to develop and initially validate a quantitative instrument that school personnel can use to determine if a student, identified as having a traumatic brain injury, will benefit from district-level consultation from a brain injury team. Three studies were designed to investigate the research questions. In study one, the planning and construction of the DORI-TBI was completed. Study two addressed the content validity of the DORI-TBI through a comparison analysis with other referral forms, content review with experts in the field of TBI, and cognitive interviews with professionals to test the usability of the new screening tool. In study three, a field administration was conducted using vignettes to measure construct validity. Results produced a valid and reliable new screening instrument that can aid school-based teams to more efficiently utilize district level consultation with a brain injury support team.

Psychometric Investigation of the Check-In, Check-Out Fidelity of Implementation Measure

Suspension and expulsion are utilized frequently and disproportionality in schools in the United States. Many schools utilize Positive Behavioral Interventions and Supports (PBIS), a tiered framework to prevent problem behavior and reduce the use of discipline practices (Sugai et al., 2000). Check-In, Check-Out (CICO) is a targeted group behavioral intervention that is utilized within this framework in schools to prevent severe problem behavior in students that are beginning to exhibit externalizing and/or internalizing behavioral needs; thus, preventing the use of exclusionary discipline practices (Crone et al., 2010; Hawken & Horner, 2003). As the use of CICO in schools continues to grow, so too does the need for an instrument measuring its fidelity of implementation. The purpose of this study was to investigate the reliability and validity of the Check-In, Check-Out Fidelity of Implementation Measure (Crone et al., 2010), an instrument created to measure the fidelity of implementation of CICO intervention. This study assessed the psychometric properties of the instrument utilizing an archival data set collected by the statewide PBIS initiative in a western state in the U.S. The results demonstrated promising content validity, construct validity, internal consistency, and interrater reliability. A unidimensional structure was determined to be the best structure for the instrument based on parsimony and the strong results obtained from the item loadings, internal consistency, and interrater reliability. Implications for use and future research are discussed.