Comparative phylogeography of two co-distributed arctic-alpine freshwater insect species in Europe

The distribution pattern of European arctic-alpine disjunct species is of growing interest among biogeographers due to the arising variety of inferred demographic histories. In this thesis I used the co-distributed mayfly Ameletus inopinatus and the stonefly Arcynopteryx compacta as model species to investigate the European Pleistocene and Holocene history of stream-inhabiting arctic-alpine aquatic insects. I used last glacial maximum (LGM) species distribution models (SDM) to derive hypotheses on the glacial survival during the LGM and the recolonization of Fennoscandia: 1) both species potentially survived glacial cycles in periglacial, extra Mediterranean refugia, and 2) postglacial recolonization of Fennoscandia originated from these refugia. I tested these hypotheses using mitochondrial sequence (mtCOI) and species specific microsatellite data. Additionally, I used future SDM to predict the impact of climate change induced range shifts and habitat loss on the overall genetic diversity of the endangered mayfly A. inopinatus.rnI observed old lineages, deep splits, and almost complete lineage sorting of mtCOI sequences between mountain ranges. These results support the hypothesis that both species persisted in multiple periglacial extra-Mediterranean refugia in Central Europe during the LGM. However, the recolonization of Fennoscandia was very different between the two study species. For the mayfly A. inopinatus I found strong differentiation between the Fennoscandian and all other populations in sequence and microsatellite data, indicating that Fennoscandia was recolonized from an extra European refugium. High mtCOI genetic structure within Fennoscandia supports a recolonization of multiple lineages from independent refugia. However, this structure was not apparent in the microsatellite data, consistent with secondary contact without sexual incompability. In contrast, the stonefly A. compacta exhibited low genetic structure and shared mtCOI haplotypes among Fennoscandia and the Black Forest, suggesting a shared Pleistocene refugium in the periglacial tundrabelt. Again, there is incongruence with the microsatellite data, which could be explained with ancestral polymorphism or female-biased dispersal. Future SDM projects major regional habitat loss for the mayfly A. inopinatus, particularly in Central European mountain ranges. By relating these range shifts to my population genetic results, I identified conservation units primarily in Eastern Europe, that if preserved would maintain high levels of the present-day genetic diversity of A. inopinatus and continue to provide long-term suitable habitat under future climate warming scenarios.rnIn this thesis I show that despite similar present day distributions the underlying demographic histories of the study species are vastly different, which might be due to differing dispersal capabilities and niche plasticity. I present genetic, climatic, and ecological data that can be used to prioritize conservation efforts for cold-adapted freshwater insects in light of future climate change. Overall, this thesis provides a next step in filling the knowledge gap regarding molecular studies of the arctic-alpine invertebrate fauna. However, there is continued need to explore the phenomenon of arctic-alpine disjunctions to help understand the processes of range expansion, regression, and lineage diversification in Europe’s high latitude and high altitude biota.

Data dissemination over complex networks through gossip

This thesis offers a practical and theoretical evaluations about gossip-epidemic algorithms, comparing those most common in the literature with new proposed algorithms and analyzing their behavior. Tests have been executed using one hundred graphs that has been randomly generated by Large Unstructured NEtwork Simulator (LUNES), a simulation software provided by Parallel and Distributed Simulation Research Group (PADS), of the Department of Computer Science, Università di Bologna and simulated using Advanced RTI System (ARTÌS), based on the High Level Architecture standard. Literatures algorithms have been analyzed and taken as base for new algorithms.

Aggregate Programming in Scala: a Core Library and Actor-Based Platform for Distributed Computational Fields

La programmazione aggregata è un paradigma che supporta la programmazione di sistemi di dispositivi, adattativi ed eventualmente a larga scala, nel loro insieme -- come aggregati. L'approccio prevalente in questo contesto è basato sul field calculus, un calcolo formale che consente di definire programmi aggregati attraverso la composizione funzionale di campi computazionali, creando i presupposti per la specifica di pattern di auto-organizzazione robusti. La programmazione aggregata è attualmente supportata, in modo più o meno parziale e principalmente per la simulazione, da DSL dedicati (cf., Protelis), ma non esistono framework per linguaggi mainstream finalizzati allo sviluppo di applicazioni. Eppure, un simile supporto sarebbe auspicabile per ridurre tempi e sforzi d'adozione e per semplificare l'accesso al paradigma nella costruzione di sistemi reali, nonché per favorire la ricerca stessa nel campo. Il presente lavoro consiste nello sviluppo, a partire da un prototipo della semantica operazionale del field calculus, di un framework per la programmazione aggregata in Scala. La scelta di Scala come linguaggio host nasce da motivi tecnici e pratici. Scala è un linguaggio moderno, interoperabile con Java, che ben integra i paradigmi ad oggetti e funzionale, ha un sistema di tipi espressivo, e fornisce funzionalità avanzate per lo sviluppo di librerie e DSL. Inoltre, la possibilità di appoggiarsi, su Scala, ad un framework ad attori solido come Akka, costituisce un altro fattore trainante, data la necessità di colmare l'abstraction gap inerente allo sviluppo di un middleware distribuito. Nell'elaborato di tesi si presenta un framework che raggiunge il triplice obiettivo: la costruzione di una libreria Scala che realizza la semantica del field calculus in modo corretto e completo, la realizzazione di una piattaforma distribuita Akka-based su cui sviluppare applicazioni, e l'esposizione di un'API generale e flessibile in grado di supportare diversi scenari.

Evaluating Code Duplication to Identify Rich Business Objects from Data Transfer Objects

Java Enterprise Applications (JEAs) are complex software systems written using multiple technologies. Moreover they are usually distributed systems and use a database to deal with persistence. A particular problem that appears in the design of these systems is the lack of a rich business model. In this paper we propose a technique to support the recovery of such rich business objects starting from anemic Data Transfer Objects (DTOs). Exposing the code duplications in the application's elements using the DTOs we suggest which business logic can be moved into the DTOs from the other classes.

Performance Modeling Of Reconfigurable Distributed Systems Based On The Opensparc Fpga Board And The Sirc Communication Framewor

This thesis explores system performance for reconfigurable distributed systems and provides an analytical model for determining throughput of theoretical systems based on the OpenSPARC FPGA Board and the SIRC Communication Framework. This model was developed by studying a small set of variables that together determine a system¿s throughput. The importance of this model is in assisting system designers to make decisions as to whether or not to commit to designing a reconfigurable distributed system based on the estimated performance and hardware costs. Because custom hardware design and distributed system design are both time consuming and costly, it is important for designers to make decisions regarding system feasibility early in the development cycle. Based on experimental data the model presented in this paper shows a close fit with less than 10% experimental error on average. The model is limited to a certain range of problems, but it can still be used given those limitations and also provides a foundation for further development of modeling reconfigurable distributed systems.

Subconductance states of Cx30 gap junction channels: data from transfected HeLa cells versus data from a mathematical model

Human HeLa cells expressing mouse connexin30 were used to study the electrical properties of gap junction channel substates. Experiments were performed on cell pairs using a dual voltage-clamp method. Single-channel currents revealed discrete levels attributable to a main state, a residual state, and five substates interposed, suggesting the operation of six subgates provided by the six connexins of a gap junction hemichannel. Substate conductances, gamma(j,substate), were unevenly distributed between the main-state and the residual-state conductance (gamma(j,main state) = 141 pS, gamma(j,residual state) = 21 pS). Activation of the first subgate reduced the channel conductance by approximately 30%, and activation of subsequent subgates resulted in conductance decrements of 10-15% each. Current transitions between the states were fast (<2 ms). Substate events were usually demarcated by transitions from and back to the main state; transitions among substates were rare. Hence, subgates are recruited simultaneously rather than sequentially. The incidence of substate events was larger at larger gradients of V(j). Frequency and duration of substate events increased with increasing number of synchronously activated subgates. Our mathematical model, which describes the operation of gap junction channels, was expanded to include channel substates. Based on the established V(j)-sensitivity of gamma(j,main state) and gamma(j,residual state), the simulation yielded unique functions gamma(j,substate) = f(V(j)) for each substate. Hence, the spacing of subconductance levels between the channel main state and residual state were uneven and characteristic for each V(j).

Percutaneous coronary interventions in Europe: prevalence, numerical estimates, and projections based on data up to 2004

AIMS: A registry mandated by the European Society of Cardiology collects data on trends in interventional cardiology within Europe. Special interest focuses on relative increases and ratios in new techniques and their distributions across Europe. We report the data through 2004 and give an overview of the development of coronary interventions since the first data collection in 1992. METHODS AND RESULTS: Questionnaires were distributed yearly to delegates of all national societies of cardiology represented in the European Society of Cardiology. The goal was to collect the case numbers of all local institutions and operators. The overall numbers of coronary angiographies increased from 1992 to 2004 from 684 000 to 2 238 000 (from 1250 to 3930 per million inhabitants). The respective numbers for percutaneous coronary interventions (PCIs) and coronary stenting procedures increased from 184 000 to 885 000 (from 335 to 1550) and from 3000 to 770 000 (from 5 to 1350), respectively. Germany was the most active country with 712 000 angiographies (8600), 249 000 angioplasties (3000), and 200 000 stenting procedures (2400) in 2004. The indication has shifted towards acute coronary syndromes, as demonstrated by rising rates of interventions for acute myocardial infarction over the last decade. The procedures are more readily performed and perceived safer, as shown by increasing rate of "ad hoc" PCIs and decreasing need for emergency coronary artery bypass grafting (CABG). In 2004, the use of drug-eluting stents continued to rise. However, an enormous variability is reported with the highest rate in Switzerland (70%). If the rate of progression remains constant until 2010 the projected number of coronary angiographies will be over three million, and the number of PCIs about 1.5 million with a stenting rate of almost 100%. CONCLUSION: Interventional cardiology in Europe is ever expanding. New coronary revascularization procedures, alternative or complementary to balloon angioplasty, have come and gone. Only stenting has stood the test of time and matured to the default technique. Facilitated access to PCI, more complete and earlier detection of coronary artery disease promise continued growth of the procedure despite the uncontested success of prevention.

DISTRIBUTED REPRODUCIBLE RESEARCH USING CACHED COMPUTATIONS

The ability to make scientific findings reproducible is increasingly important in areas where substantive results are the product of complex statistical computations. Reproducibility can allow others to verify the published findings and conduct alternate analyses of the same data. A question that arises naturally is how can one conduct and distribute reproducible research? This question is relevant from the point of view of both the authors who want to make their research reproducible and readers who want to reproduce relevant findings reported in the scientific literature. We present a framework in which reproducible research can be conducted and distributed via cached computations and describe specific tools for both authors and readers. As a prototype implementation we introduce three software packages written in the R language. The cacheSweave and stashR packages together provide tools for caching computational results in a key-value style database which can be published to a public repository for readers to download. The SRPM package provides tools for generating and interacting with "shared reproducibility packages" (SRPs) which can facilitate the distribution of the data and code. As a case study we demonstrate the use of the toolkit on a national study of air pollution exposure and mortality.

Bayesian Hierarchical Distributed Lag Models for Summer Ozone Exposure and Cardio-Respiratory Mortality

In this paper, we develop Bayesian hierarchical distributed lag models for estimating associations between daily variations in summer ozone levels and daily variations in cardiovascular and respiratory (CVDRESP) mortality counts for 19 U.S. large cities included in the National Morbidity Mortality Air Pollution Study (NMMAPS) for the period 1987 - 1994. At the first stage, we define a semi-parametric distributed lag Poisson regression model to estimate city-specific relative rates of CVDRESP associated with short-term exposure to summer ozone. At the second stage, we specify a class of distributions for the true city-specific relative rates to estimate an overall effect by taking into account the variability within and across cities. We perform the calculations with respect to several random effects distributions (normal, t-student, and mixture of normal), thus relaxing the common assumption of a two-stage normal-normal hierarchical model. We assess the sensitivity of the results to: 1) lag structure for ozone exposure; 2) degree of adjustment for long-term trends; 3) inclusion of other pollutants in the model;4) heat waves; 5) random effects distributions; and 6) prior hyperparameters. On average across cities, we found that a 10ppb increase in summer ozone level for every day in the previous week is associated with 1.25 percent increase in CVDRESP mortality (95% posterior regions: 0.47, 2.03). The relative rate estimates are also positive and statistically significant at lags 0, 1, and 2. We found that associations between summer ozone and CVDRESP mortality are sensitive to the confounding adjustment for PM_10, but are robust to: 1) the adjustment for long-term trends, other gaseous pollutants (NO_2, SO_2, and CO); 2) the distributional assumptions at the second stage of the hierarchical model; and 3) the prior distributions on all unknown parameters. Bayesian hierarchical distributed lag models and their application to the NMMAPS data allow us estimation of an acute health effect associated with exposure to ambient air pollution in the last few days on average across several locations. The application of these methods and the systematic assessment of the sensitivity of findings to model assumptions provide important epidemiological evidence for future air quality regulations.

A BAYESIAN HIERARCHICAL MODEL FOR CONSTRAINED DISTRIBUTED LAG FUNCTIONS: ESTIMATING THE TIME COURSE OF HOSPITALIZATION ASSOCIATED WITH AIR POLLUTION EXPOSURE

Numerous time series studies have provided strong evidence of an association between increased levels of ambient air pollution and increased levels of hospital admissions, typically at 0, 1, or 2 days after an air pollution episode. An important research aim is to extend existing statistical models so that a more detailed understanding of the time course of hospitalization after exposure to air pollution can be obtained. Information about this time course, combined with prior knowledge about biological mechanisms, could provide the basis for hypotheses concerning the mechanism by which air pollution causes disease. Previous studies have identified two important methodological questions: (1) How can we estimate the shape of the distributed lag between increased air pollution exposure and increased mortality or morbidity? and (2) How should we estimate the cumulative population health risk from short-term exposure to air pollution? Distributed lag models are appropriate tools for estimating air pollution health effects that may be spread over several days. However, estimation for distributed lag models in air pollution and health applications is hampered by the substantial noise in the data and the inherently weak signal that is the target of investigation. We introduce an hierarchical Bayesian distributed lag model that incorporates prior information about the time course of pollution effects and combines information across multiple locations. The model has a connection to penalized spline smoothing using a special type of penalty matrix. We apply the model to estimating the distributed lag between exposure to particulate matter air pollution and hospitalization for cardiovascular and respiratory disease using data from a large United States air pollution and hospitalization database of Medicare enrollees in 94 counties covering the years 1999-2002.

The zebrafish, brain-specific, aromatase cyp19a2 is neither expressed nor distributed in a sexually dimorphic manner during sexual differentiation

Differential cyp19 aromatase expression during development leads to sexual dimorphisms in the mammalian brain. Whether this is also true for fish is unknown. The aim of the current study has been to follow the expression of the brain-specific aromatase cyp19a2 in the brains of sexually differentiating zebrafish. To assess the role of cyp19a2 in the zebrafish brain during gonadal differentiation, we used quantitative reverse transcriptase-polymerase chain reaction and immunohistochemistry to detect differences in the transcript or protein levels and/or expression pattern in juvenile fish, histology to monitor the gonadal status, and double immunofluorescence with neuronal or radial glial markers to characterize aromatase-positive cells. Our data show that cyp19a2 expression levels during zebrafish sexual differentiation cannot be assigned to a particular sex; the expression pattern in the brain is similar in both sexes and aromatase-positive cells appear to be mostly of radial glial nature.

From Statistical Data to Spatial Knowledge - informing decision making in Vietnam

Vietnam has developed rapidly over the past 15 years. However, progress was not uniformly distributed across the country. Availability, adequate visualization and analysis of spatially explicit data on socio-economic and environmental aspects can support both research and policy towards sustainable development. Applying appropriate mapping techniques allows gleaning important information from tabular socio-economic data. Spatial analysis of socio-economic phenomena can yield insights into locally-specifi c patterns and processes that cannot be generated by non-spatial applications. This paper presents techniques and applications that develop and analyze spatially highly disaggregated socioeconomic datasets. A number of examples show how such information can support informed decisionmaking and research in Vietnam.

Detection of complex point targets with distributed assets in a MIMO radar system

The report explores the problem of detecting complex point target models in a MIMO radar system. A complex point target is a mathematical and statistical model for a radar target that is not resolved in space, but exhibits varying complex reflectivity across the different bistatic view angles. The complex reflectivity can be modeled as a complex stochastic process whose index set is the set of all the bistatic view angles, and the parameters of the stochastic process follow from an analysis of a target model comprising a number of ideal point scatterers randomly located within some radius of the targets center of mass. The proposed complex point targets may be applicable to statistical inference in multistatic or MIMO radar system. Six different target models are summarized here – three 2-dimensional (Gaussian, Uniform Square, and Uniform Circle) and three 3-dimensional (Gaussian, Uniform Cube, and Uniform Sphere). They are assumed to have different distributions on the location of the point scatterers within the target. We develop data models for the received signals from such targets in the MIMO radar system with distributed assets and partially correlated signals, and consider the resulting detection problem which reduces to the familiar Gauss-Gauss detection problem. We illustrate that the target parameter and transmit signal have an influence on the detector performance through target extent and the SNR respectively. A series of the receiver operator characteristic (ROC) curves are generated to notice the impact on the detector for varying SNR. Kullback–Leibler (KL) divergence is applied to obtain the approximate mean difference between density functions the scatterers assume inside the target models to show the change in the performance of the detector with target extent of the point scatterers.

Hermitian curve interpolation for CT-data re-sampling

Purpose: Development of an interpolation algorithm for re‐sampling spatially distributed CT‐data with the following features: global and local integral conservation, avoidance of negative interpolation values for positively defined datasets and the ability to control re‐sampling artifacts. Method and Materials: The interpolation can be separated into two steps: first, the discrete CT‐data has to be continuously distributed by an analytic function considering the boundary conditions. Generally, this function is determined by piecewise interpolation. Instead of using linear or high order polynomialinterpolations, which do not fulfill all the above mentioned features, a special form of Hermitian curve interpolation is used to solve the interpolation problem with respect to the required boundary conditions. A single parameter is determined, by which the behavior of the interpolation function is controlled. Second, the interpolated data have to be re‐distributed with respect to the requested grid. Results: The new algorithm was compared with commonly used interpolation functions based on linear and second order polynomial. It is demonstrated that these interpolation functions may over‐ or underestimate the source data by about 10%–20% while the parameter of the new algorithm can be adjusted in order to significantly reduce these interpolation errors. Finally, the performance and accuracy of the algorithm was tested by re‐gridding a series of X‐ray CT‐images. Conclusion: Inaccurate sampling values may occur due to the lack of integral conservation. Re‐sampling algorithms using high order polynomialinterpolation functions may result in significant artifacts of the re‐sampled data. Such artifacts can be avoided by using the new algorithm based on Hermitian curve interpolation

Distributed Repositories for Educational Content

As education providers increasingly integrate digital learning media into their education processes, the need for the systematic management of learning materials and learning arrangements becomes clearer. Digital repositories, often called Learning Object Repositories (LOR), promise to provide an answer to this challenge. This article is composed of two parts. In this part, we derive technological and pedagogical requirements for LORs from a concretization of information quality criteria for e-learning technology. We review the evolution of learning object repositories and discuss their core features in the context of pedagogical requirements, information quality demands, and e-learning technology standards. We conclude with an outlook in Part 2, which presents concrete technical solutions, in particular networked repository architectures.