Quantitative integration of high-resolution hydrogeophysical data through Monte-Carlo-type conditional simulations

Geophysical techniques can help to bridge the inherent gap with regard to spatial resolution and the range of coverage that plagues classical hydrological methods. This has lead to the emergence of the new and rapidly growing field of hydrogeophysics. Given the differing sensitivities of various geophysical techniques to hydrologically relevant parameters and their inherent trade-off between resolution and range the fundamental usefulness of multi-method hydrogeophysical surveys for reducing uncertainties in data analysis and interpretation is widely accepted. A major challenge arising from such endeavors is the quantitative integration of the resulting vast and diverse database in order to obtain a unified model of the probed subsurface region that is internally consistent with all available data. To address this problem, we have developed a strategy towards hydrogeophysical data integration based on Monte-Carlo-type conditional stochastic simulation that we consider to be particularly suitable for local-scale studies characterized by high-resolution and high-quality datasets. Monte-Carlo-based optimization techniques are flexible and versatile, allow for accounting for a wide variety of data and constraints of differing resolution and hardness and thus have the potential of providing, in a geostatistical sense, highly detailed and realistic models of the pertinent target parameter distributions. Compared to more conventional approaches of this kind, our approach provides significant advancements in the way that the larger-scale deterministic information resolved by the hydrogeophysical data can be accounted for, which represents an inherently problematic, and as of yet unresolved, aspect of Monte-Carlo-type conditional simulation techniques. We present the results of applying our algorithm to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the local-scale porosity structure. Our procedure is first tested on pertinent synthetic data and then applied to corresponding field data collected at the Boise Hydrogeophysical Research Site near Boise, Idaho, USA.

Systems Genetics of Metabolism: The Use of the BXD Murine Reference Panel for Multiscalar Integration of Traits.

Metabolic homeostasis is achieved by complex molecular and cellular networks that differ significantly among individuals and are difficult to model with genetically engineered lines of mice optimized to study single gene function. Here, we systematically acquired metabolic phenotypes by using the EUMODIC EMPReSS protocols across a large panel of isogenic but diverse strains of mice (BXD type) to study the genetic control of metabolism. We generated and analyzed 140 classical phenotypes and deposited these in an open-access web service for systems genetics (www.genenetwork.org). Heritability, influence of sex, and genetic modifiers of traits were examined singly and jointly by using quantitative-trait locus (QTL) and expression QTL-mapping methods. Traits and networks were linked to loci encompassing both known variants and novel candidate genes, including alkaline phosphatase (ALPL), here linked to hypophosphatasia. The assembled and curated phenotypes provide key resources and exemplars that can be used to dissect complex metabolic traits and disorders.

Quantitative genetics of learning ability and resistance to stress in Drosophila melanogaster.

Even though laboratory evolution experiments have demonstrated genetic variation for learning ability, we know little about the underlying genetic architecture and genetic relationships with other ecologically relevant traits. With a full diallel cross among twelve inbred lines of Drosophila melanogaster originating from a natural population (0.75 < F < 0.93), we investigated the genetic architecture of olfactory learning ability and compared it to that for another behavioral trait (unconditional preference for odors), as well as three traits quantifying the ability to deal with environmental challenges: egg-to-adult survival and developmental rate on a low-quality food, and resistance to a bacterial pathogen. Substantial additive genetic variation was detected for each trait, highlighting their potential to evolve. Genetic effects contributed more than nongenetic parental effects to variation in traits measured at the adult stage: learning, odorant perception, and resistance to infection. In contrast, the two traits quantifying larval tolerance to low-quality food were more strongly affected by parental effects. We found no evidence for genetic correlations between traits, suggesting that these traits could evolve at least to some degree independently of one another. Finally, inbreeding adversely affected all traits.

Promotion of learning skills in the study of economics. pilot project in the subject area of

This communication is part of a larger teaching innovation project financed by the University ofBarcelona, whose objective is to develop and evaluate transversal competences of the UB, learningability and responsibility. The competence is divided into several sub-competencies being the ability toanalyze and synthesis the most intensely worked in the first year. The work presented here part fromthe results obtained in phase 1 and 2 previously implemented in other subjects (Mathematics andHistory) in the first year of the degree of Business Administration Degree. In these subjects’ previousexperiences there were deficiencies in the acquisition of learning skills by the students. The work inthe subject of Mathematics facilitated that students become aware of the deficit. The work on thesubject of History insisted on developing readings schemes and with the practical exercises wassought to go deeply in the development of this competence.The third phase presented here is developed in the framework of the second year degree, in the WorldEconomy subject. The objective of this phase is the development and evaluation of the same crosscompetence of the previous phases, from a practice that includes both, quantitative analysis andcritical reflection. Specifically the practice focuses on the study of the dynamic relationship betweeneconomic growth and the dynamics in the distribution of wealth. The activity design as well as theselection of materials to make it, has been directed to address gaps in the ability to analyze andsynthesize detected in the subjects of the first year in the previous phases of the project.The realization of the practical case is considered adequate methodology to improve the acquisition ofcompetence of the students, then it is also proposed how to evaluate the acquisition of suchcompetence. The practice is evaluated based on a rubric developed in the framework of the projectobjectives. Thus at the end of phase 3 we can analyze the process that have followed the students,detect where they have had major difficulties and identify those aspects of teaching that can help toimprove the acquisition of skills by the students. The interest of this phase resides in the possibility tovalue whether tracing of learning through competences, organized in a collaborative way, is a goodtool to develop the acquisition of these skills and facilitate their evaluation.

On learning dynamics underlying the evolution of learning rules.

In order to understand the development of non-genetically encoded actions during an animal's lifespan, it is necessary to analyze the dynamics and evolution of learning rules producing behavior. Owing to the intrinsic stochastic and frequency-dependent nature of learning dynamics, these rules are often studied in evolutionary biology via agent-based computer simulations. In this paper, we show that stochastic approximation theory can help to qualitatively understand learning dynamics and formulate analytical models for the evolution of learning rules. We consider a population of individuals repeatedly interacting during their lifespan, and where the stage game faced by the individuals fluctuates according to an environmental stochastic process. Individuals adjust their behavioral actions according to learning rules belonging to the class of experience-weighted attraction learning mechanisms, which includes standard reinforcement and Bayesian learning as special cases. We use stochastic approximation theory in order to derive differential equations governing action play probabilities, which turn out to have qualitative features of mutator-selection equations. We then perform agent-based simulations to find the conditions where the deterministic approximation is closest to the original stochastic learning process for standard 2-action 2-player fluctuating games, where interaction between learning rules and preference reversal may occur. Finally, we analyze a simplified model for the evolution of learning in a producer-scrounger game, which shows that the exploration rate can interact in a non-intuitive way with other features of co-evolving learning rules. Overall, our analyses illustrate the usefulness of applying stochastic approximation theory in the study of animal learning.

GPS to LRM: Integration of Spatial Point Features with Linear Referencing Methods, 2001

Global positioning systems (GPS) offer a cost-effective and efficient method to input and update transportation data. The spatial location of objects provided by GPS is easily integrated into geographic information systems (GIS). The storage, manipulation, and analysis of spatial data are also relatively simple in a GIS. However, many data storage and reporting methods at transportation agencies rely on linear referencing methods (LRMs); consequently, GPS data must be able to link with linear referencing. Unfortunately, the two systems are fundamentally incompatible in the way data are collected, integrated, and manipulated. In order for the spatial data collected using GPS to be integrated into a linear referencing system or shared among LRMs, a number of issues need to be addressed. This report documents and evaluates several of those issues and offers recommendations. In order to evaluate the issues associated with integrating GPS data with a LRM, a pilot study was created. To perform the pilot study, point features, a linear datum, and a spatial representation of a LRM were created for six test roadway segments that were located within the boundaries of the pilot study conducted by the Iowa Department of Transportation linear referencing system project team. Various issues in integrating point features with a LRM or between LRMs are discussed and recommendations provided. The accuracy of the GPS is discussed, including issues such as point features mapping to the wrong segment. Another topic is the loss of spatial information that occurs when a three-dimensional or two-dimensional spatial point feature is converted to a one-dimensional representation on a LRM. Recommendations such as storing point features as spatial objects if necessary or preserving information such as coordinates and elevation are suggested. The lack of spatial accuracy characteristic of most cartography, on which LRM are often based, is another topic discussed. The associated issues include linear and horizontal offset error. The final topic discussed is some of the issues in transferring point feature data between LRMs.

Stage-specific integration of maternal and embryonic peroxisome proliferator-activated receptor delta signaling is critical to pregnancy success.

Successful pregnancy depends on well coordinated developmental events involving both maternal and embryonic components. Although a host of signaling pathways participate in implantation, decidualization, and placentation, whether there is a common molecular link that coordinates these processes remains unknown. By exploiting genetic, molecular, pharmacological, and physiological approaches, we show here that the nuclear transcription factor peroxisome proliferator-activated receptor (PPAR) delta plays a central role at various stages of pregnancy, whereas maternal PPARdelta is critical to implantation and decidualization, and embryonic PPARdelta is vital for placentation. Using trophoblast stem cells, we further elucidate that a reciprocal relationship between PPARdelta-AKT and leukemia inhibitory factor-STAT3 signaling pathways serves as a cell lineage sensor to direct trophoblast cell fates during placentation. This novel finding of stage-specific integration of maternal and embryonic PPARdelta signaling provides evidence that PPARdelta is a molecular link that coordinates implantation, decidualization, and placentation crucial to pregnancy success. This study is clinically relevant because deferral of on time implantation leads to spontaneous pregnancy loss, and defective trophoblast invasion is one cause of preeclampsia in humans.

Integration of Notch 1 and calcineurin/NFAT signaling pathways in keratinocyte growth and differentiation control.

The Notch and Calcineurin/NFAT pathways have both been implicated in control of keratinocyte differentiation. Induction of the p21(WAF1/Cip1) gene by Notch 1 activation in differentiating keratinocytes is associated with direct targeting of the RBP-Jkappa protein to the p21 promoter. We show here that Notch 1 activation functions also through a second Calcineurin-dependent mechanism acting on the p21 TATA box-proximal region. Increased Calcineurin/NFAT activity by Notch signaling involves downregulation of Calcipressin, an endogenous Calcineurin inhibitor, through a HES-1-dependent mechanism. Besides control of the p21 gene, Calcineurin contributes significantly to the transcriptional response of keratinocytes to Notch 1 activation, both in vitro and in vivo. In fact, deletion of the Calcineurin B1 gene in the skin results in a cyclic alopecia phenotype, associated with altered expression of Notch-responsive genes involved in hair follicle structure and/or adhesion to the surrounding mesenchyme. Thus, an important interconnection exists between Notch 1 and Calcineurin-NFAT pathways in keratinocyte growth/differentiation control.

Improving Searching and Browsing Capabilities of Learning Object Repositories

Learning object repositories are a basic piece of virtual learning environments used for content management. Nevertheless, learning objects have special characteristics that make traditional solutions for content management ine ective. In particular, browsing and searching for learning objects cannot be based on the typical authoritative meta-data used for describing content, such as author, title or publicationdate, among others. We propose to build a social layer on top of a learning object repository, providing nal users with additional services fordescribing, rating and curating learning objects from a teaching perspective. All these interactions among users, services and resources can be captured and further analyzed, so both browsing and searching can be personalized according to user pro le and the educational context, helping users to nd the most valuable resources for their learning process. In this paper we propose to use reputation schemes and collaborative filtering techniques for improving the user interface of a DSpace based learning object repository.

From institutional repositories to personal collections of learning resources

Institutional digital repositories are a basic piece to provide preservation and reutilization of learning resources. However, their creation and maintenance is usually performed following a top-down approach, causing limitations in the search and reutilization of learning resources. In order to avoid this problem we propose to use web 2.0 functionalities. In this paper we present how tagging can be used to enhance the search and reusability functionalities of institutional learning repositories as well as promoting their usage. The paper also describes the evaluation process that was performed in a pilot experience involving open educational resources.

Integration of a 3D rendering engine with a physics simulator

The goal of this project is the integration of a set of technologies (graphics, physical simulation, input), with the azm of assembling an application framework in phyton. In this research, a set of key introductory concepts are presented in adoption of a deep study of the state of the art of 3D applications. Phyton is selected an justified as the programing language due to the features and advantages that it offers in front of other languages. Finally the design and implementation of the framework is presented in the last chapter with some client application examples.

Interoperability of learning objects copyright in the LUISA semantic learning management system

Semantic Web technology is able to provide the required computational semantics for interoperability of learning resources across different Learning Management Systems (LMS) and Learning Object Repositories (LOR). The EU research project LUISA (Learning Content Management System Using Innovative Semantic Web Services Architecture) addresses the development of a reference semantic architecture for the major challenges in the search, interchange and delivery of learning objects in a service-oriented context. One of the key issues, highlighted in this paper, is Digital Rights Management (DRM) interoperability. A Semantic Web approach to copyright management has been followed, which places a Copyright Ontology as the key component for interoperability among existing DRM systems and other licensing schemes like Creative Commons. Moreover, Semantic Web tools like reasoners, rule engines and semantic queries facilitate the implementation of an interoperable copyright management component in the LUISA architecture.

Integration of Economics into Life Cycle Assessment in the Finnish Pulp and Paper Industry

Taloudellisen laskennan yhdistäminen elinkaariarviointiin (LCA) on alkanut kiinnostaa eri teollisuuden aloja maailmanlaajuisesti viime aikoina. Useat LCA-tietokoneohjelmat sisältävät kustannuslaskentaominaisuuksia ja yksittäiset projektit ovat yhdistäneet ympäristö- ja talouslaskentamenetelmiä. Tässä projektissa tutkitaan näiden yhdistelmien soveltuvuutta suomalaiselle sellu- ja paperiteollisuudelle, sekä kustannuslaskentaominaisuuden lisäämistä KCL:n LCA-ohjelmaan, KCL-ECO 3.0:aan. Kaikki tutkimuksen aikana löytyneet menetelmät, jotka yhdistävät LCA:n ja taloudellista laskentaa, on esitelty tässä työssä. Monet näistä käyttävät elinkaarikustannusarviointia (LCCA). Periaatteessa elinkaari määritellään eri tavalla LCCA:ssa ja LCA:ssa, mikä luo haasteita näiden menetelmien yhdistämiselle. Sopiva elinkaari tulee määritellä laskennan tavoitteiden mukaisesti. Työssä esitellään suositusmenetelmä, joka lähtee suomalaisen sellu- ja paperiteollisuuden erikoispiirteistä. Perusvaatimuksena on yhteensopivuus tavanomaisesti paperin LCA:ssa käytetyn elinkaaren kanssa. Menetelmän yhdistäminen KCL-ECO 3.0:aan on käsitelty yksityiskohtaisesti.