A demonstration case on the derivation of process-level logical architectures for ambient assisted living ecosystems

When representing the requirements for an intended software solution during the development process, a logical architecture is a model that provides an organized vision of how functionalities behave regardless of the technologies to be implemented. If the logical architecture represents an ambient assisted living (AAL) ecosystem, such representation is a complex task due to the existence of interrelated multidomains, which, most of the time, results in incomplete and incoherent user requirements. In this chap- ter, we present the results obtained when applying process-level modeling techniques to the derivation of the logical architecture for a real industrial AAL project. We adopt a V-Model–based approach that expresses the AAL requirements in a process-level perspec- tive, instead of the traditional product-level view. Additionally, we ensure compliance of the derived logical architecture with the National Institute of Standards and Technology (NIST) reference architecture as nonfunctional requirements to support the implementa- tion of the AAL architecture in cloud contexts.

Modelación de la distribución de especies y ecosistemas en el tiempo y en el espacio: una revisión de las nuevas herramientas y enfoques disponibles

This article aims to present the conceptual and methodological framework in which models techniques for species and ecosystems distribution are developed. An historical review of concepts behind these techniques is made as well as the presentation of the major methodological steps involved in these tests. A discussion on how these approaches are useful for the development of new questions in the field of biogeography and biological conservation is generated. Finally, an application of distribution modeling techniques, using the specie Beilschmiedia miersii (belloto Del Norte) as a study case, is presented. This conceptual and methodological review as well as the example applied, seeks to clarify the usefulness and potential of distribution models techniques, with the objective to go forward in biogeography research and thus, farther progress in understanding spatial and temporal patterns of organism's distribution

An ecoregional classification for the state of Roraima, Brazil: the importance of landscape in malaria biology

Understanding the different background landscapes in which malaria transmission occurs is fundamental to understanding malaria epidemiology and to designing effective local malaria control programs. Geology, geomorphology, vegetation, climate, land use, and anopheline distribution were used as a basis for an ecological classification of the state of Roraima, Brazil, in the northern Amazon Basin, focused on the natural history of malaria and transmission. We used unsupervised maximum likelihood classification, principal components analysis, and weighted overlay with equal contribution analyses to fine-scale thematic maps that resulted in clustered regions. We used ecological niche modeling techniques to develop a fine-scale picture of malaria vector distributions in the state. Eight ecoregions were identified and malaria-related aspects are discussed based on this classification, including 5 types of dense tropical rain forest and 3 types of savannah. Ecoregions formed by dense tropical rain forest were named as montane (ecoregion I), submontane (II), plateau (III), lowland (IV), and alluvial (V). Ecoregions formed by savannah were divided into steppe (VI, campos de Roraima), savannah (VII, cerrado), and wetland (VIII, campinarana). Such ecoregional mappings are important tools in integrated malaria control programs that aim to identify specific characteristics of malaria transmission, classify transmission risk, and define priority areas and appropriate interventions. For some areas, extension of these approaches to still-finer resolutions will provide an improved picture of malaria transmission patterns.

Horizontal, but not vertical, biotic interactions affect fine-scale plant distribution patterns in a low-energy system

Studies of species range determinants have traditionally focused on abiotic variables (typically climatic conditions), and therefore the recent explicit consideration of biotic interactions represents an important advance in the field. While these studies clearly support the role of biotic interactions in shaping species distributions, most examine only the influence of a single species and/or a single interaction, failing to account for species being subject to multiple concurrent interactions. By fitting species distribution models (SDMs), we examine the influence of multiple vertical (i.e., grazing, trampling, and manuring by mammalian herbivores) and horizontal (i.e., competition and facilitation; estimated from the cover of dominant plant species) interspecific interactions on the occurrence and cover of 41 alpine tundra plant species. Adding plant-plant interactions to baseline SDMs (using five field-quantified abiotic variables) significantly improved models' predictive power for independent data, while herbivore-related variables had only a weak influence. Overall, abiotic variables had the strongest individual contributions to the distribution of alpine tundra plants, with the importance of horizontal interaction variables exceeding that of vertical interaction variables. These results were consistent across three modeling techniques, for both species occurrence and cover, demonstrating the pattern to be robust. Thus, the explicit consideration of multiple biotic interactions reveals that plant-plant interactions exert control over the fine-scale distribution of vascular species that is comparable to abiotic drivers and considerably stronger than herbivores in this low-energy system.

Measuring ecological niche overlap from occurrence and spatial environmental data

1. Aim - Concerns over how global change will influence species distributions, in conjunction with increased emphasis on understanding niche dynamics in evolutionary and community contexts, highlight the growing need for robust methods to quantify niche differences between or within taxa. We propose a statistical framework to describe and compare environmental niches from occurrence and spatial environmental data.¦2. Location - Europe, North America, South America¦3. Methods - The framework applies kernel smoothers to densities of species occurrence in gridded environmental space to calculate metrics of niche overlap and test hypotheses regarding niche conservatism. We use this framework and simulated species with predefined distributions and amounts of niche overlap to evaluate several ordination and species distribution modeling techniques for quantifying niche overlap. We illustrate the approach with data on two well-studied invasive species.¦4. Results - We show that niche overlap can be accurately detected with the framework when variables driving the distributions are known. The method is robust to known and previously undocumented biases related to the dependence of species occurrences on the frequency of environmental conditions that occur across geographic space. The use of a kernel smoother makes the process of moving from geographical space to multivariate environmental space independent of both sampling effort and arbitrary choice of resolution in environmental space. However, the use of ordination and species distribution model techniques for selecting, combining and weighting variables on which niche overlap is calculated provide contrasting results.¦5. Main conclusions - The framework meets the increasing need for robust methods to quantify niche differences. It is appropriate to study niche differences between species, subspecies or intraspecific lineages that differ in their geographical distributions. Alternatively, it can be used to measure the degree to which the environmental niche of a species or intraspecific lineage has changed over time.

Rockfall characterisation and structural protection: A review

Rockfall is an extremely rapid process involving long travel distances. Due to these features, when an event occurs, the ability to take evasive action is practically zero and, thus, the risk of injury or loss of life is high. Damage to buildings and infrastructure is quite likely. In many cases, therefore, suitable protection measures are necessary. This contribution provides an overview of previous and current research on the main topics related to rockfall. It covers the onset of rockfall and runout modelling approaches, as well as hazard zoning and protection measures. It is the aim of this article to provide an in-depth knowledge base for researchers and practitioners involved in projects dealing with the rockfall protection of infrastructures, who may work in the fields of civil or environmental engineering, risk and safety, the earth and natural sciences.

Prospective sampling based on model ensembles improves the detection of rare species

Identifying the geographic distribution of populations is a basic, yet crucial step in many fundamental and applied ecological projects, as it provides key information on which many subsequent analyses depend. However, this task is often costly and time consuming, especially where rare species are concerned and where most sampling designs generally prove inefficient. At the same time, rare species are those for which distribution data are most needed for their conservation to be effective. To enhance fieldwork sampling, model-based sampling (MBS) uses predictions from species distribution models: when looking for the species in areas of high habitat suitability, chances should be higher to find them. We thoroughly tested the efficiency of MBS by conducting an important survey in the Swiss Alps, assessing the detection rate of three rare and five common plant species. For each species, habitat suitability maps were produced following an ensemble modeling framework combining two spatial resolutions and two modeling techniques. We tested the efficiency of MBS and the accuracy of our models by sampling 240 sites in the field (30 sitesx8 species). Across all species, the MBS approach proved to be effective. In particular, the MBS design strictly led to the discovery of six sites of presence of one rare plant, increasing chances to find this species from 0 to 50%. For common species, MBS doubled the new population discovery rates as compared to random sampling. Habitat suitability maps coming from the combination of four individual modeling methods predicted well the species' distribution and more accurately than the individual models. As a conclusion, using MBS for fieldwork could efficiently help in increasing our knowledge of rare species distribution. More generally, we recommend using habitat suitability models to support conservation plans.

A connectome-based comparison of diffusion MRI schemes.

Diffusion MRI has evolved towards an important clinical diagnostic and research tool. Though clinical routine is using mainly diffusion weighted and tensor imaging approaches, Q-ball imaging and diffusion spectrum imaging techniques have become more widely available. They are frequently used in research-oriented investigations in particular those aiming at measuring brain network connectivity. In this work, we aim at assessing the dependency of connectivity measurements on various diffusion encoding schemes in combination with appropriate data modeling. We process and compare the structural connection matrices computed from several diffusion encoding schemes, including diffusion tensor imaging, q-ball imaging and high angular resolution schemes, such as diffusion spectrum imaging with a publically available processing pipeline for data reconstruction, tracking and visualization of diffusion MR imaging. The results indicate that the high angular resolution schemes maximize the number of obtained connections when applying identical processing strategies to the different diffusion schemes. Compared to the conventional diffusion tensor imaging, the added connectivity is mainly found for pathways in the 50-100mm range, corresponding to neighboring association fibers and long-range associative, striatal and commissural fiber pathways. The analysis of the major associative fiber tracts of the brain reveals striking differences between the applied diffusion schemes. More complex data modeling techniques (beyond tensor model) are recommended 1) if the tracts of interest run through large fiber crossings such as the centrum semi-ovale, or 2) if non-dominant fiber populations, e.g. the neighboring association fibers are the subject of investigation. An important finding of the study is that since the ground truth sensitivity and specificity is not known, the comparability between results arising from different strategies in data reconstruction and/or tracking becomes implausible to understand.

Runkoelementtitehtaan materiaalitoimintojen kehittäminen prosessiajattelun näkökulmasta

Työn tavoitteena on ollut selvittää runkoelementtitehtaan materiaalien hankinnanorganisointi ja ohjaus nykytilanteessa. Tutkimuksessa on pyritty löytämään materiaaliprosessin kannalta toimintaa rajoittavia pullonkauloja sekä etsitty kehitystoimenpiteitä ongelmakohtiin prosessiajattelun näkökulmasta. Tarkastelun kohteena on ollut yrityksen operatiivinen materiaaliprosessi nimikkeiden tilauksesta varastointiin. Työssä on käytetty kvalitatiivista tutkimusmenetelmää ja empiirisen osuuden tiedot on hankittu haastatteluilla ja laatuohjeistuksesta. Yrityksen nykytilanne on mallinnettu prosessikaavioiden avulla, ja on selvitetty mitkä ovat prosessin tieto- ja materiaalivirrat sekä mitkä ovat tärkeimmät toiminnot materiaaliketjussa. Prosessianalyysin ja haastatteluiden pohjalta määriteltiin kehitysehdotukset prosessin suorituskyvyn tehostamiseksi. Nykytilan kartoituksen jälkeen suurimmat ongelmat materiaaliprosessissa liittyvät tilausten ajoitusten hallintaan, muutoksien vaikutukseen prosessissa sekä vastuiden ja kokonaishallinnan puuttumiseen. Ongelmat johtuvat pääosin rakennusalan projektimaisesta luonteesta. Yhdeksi kehityskohteeksi nousi myös tiedonhallinnan tehostaminen, etenkin prosessin vaiheiden automatisointi tietojärjestelmiä hyödyntäen. Toimintaan on pyritty etsimään ratkaisuja prosessiajattelun avulla, mikä osoittautui sopivaksi menetelmäksi toiminnan kehittämisessä. Tutkimuksen tuloksena syntyi kehitysehdotuksia, joiden pohjalta muodostettiin uusi materiaalien ohjauksen toimintamalli. Toimintamallissa tärkeimpänä on ennakkotiedon hyödyntäminen tilaussuunnittelun tukena. Alustavat materiaalimäärät välitetään ennakkotietona myös toimittajille, jotka voivat paremmin suunnitella omaa tuotantokapasiteettiaan. Tilausten suunnittelu tapahtuu tarkentuvasti ja lopullinen materiaalimäärä ja tarveajankohta välitetään kotiinkutsun yhteydessä. Toimintamalliin liittyy lisäksi materiaalien vastaanoton ja varastoinnin kehittäminen sekä muutoksien hallinta tietojärjestelmää paremmin hyödyntäen. Kriittisintä materiaaliprosessissa tulee olemaan prosessin tiedonhallinta ja siihen liittyvät vastuukysymykset.

In silico pathway reconstruction: Iron-sulfur cluster biogenesis in Saccharomyces cerevisiae

Background: Current advances in genomics, proteomics and other areas of molecular biology make the identification and reconstruction of novel pathways an emerging area of great interest. One such class of pathways is involved in the biogenesis of Iron-Sulfur Clusters (ISC). Results: Our goal is the development of a new approach based on the use and combination of mathematical, theoretical and computational methods to identify the topology of a target network. In this approach, mathematical models play a central role for the evaluation of the alternative network structures that arise from literature data-mining, phylogenetic profiling, structural methods, and human curation. As a test case, we reconstruct the topology of the reaction and regulatory network for the mitochondrial ISC biogenesis pathway in S. cerevisiae. Predictions regarding how proteins act in ISC biogenesis are validated by comparison with published experimental results. For example, the predicted role of Arh1 and Yah1 and some of the interactions we predict for Grx5 both matches experimental evidence. A putative role for frataxin in directly regulating mitochondrial iron import is discarded from our analysis, which agrees with also published experimental results. Additionally, we propose a number of experiments for testing other predictions and further improve the identification of the network structure. Conclusion: We propose and apply an iterative in silico procedure for predictive reconstruction of the network topology of metabolic pathways. The procedure combines structural bioinformatics tools and mathematical modeling techniques that allow the reconstruction of biochemical networks. Using the Iron Sulfur cluster biogenesis in S. cerevisiae as a test case we indicate how this procedure can be used to analyze and validate the network model against experimental results. Critical evaluation of the obtained results through this procedure allows devising new wet lab experiments to confirm its predictions or provide alternative explanations for further improving the models.

Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models

Background: Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results: Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions: Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.

Fusion weld metal solidification:Continuum from weld interface to centerline

We present a brief résumé of the history of solidification research and key factors affecting the solidification of fusion welds. There is a general agreement of the basic solidification theory, albeit differing - even confusing - nomenclatures do exist, and Cases 2 and 3 (the Chalmers' basic boundary conditions for solidification, categorized by Savage as Cases) are variably emphasized. Model Frame, a tool helping to model the continuum of fusion weld solidification from start to end, is proposed. It incorporates the general solidification models, of which the pertinent ones are selected for the actual modeling. The basic models are the main solidification Cases 1…4. These discrete Cases are joined with Sub-Cases: models of Pfann, Flemings and others, bringing needed Sub-Case variables into the model. Model Frame depicts a grain growing from the weld interface to its centerline. Besides modeling, the Model Frame supports education and academic debate. The new mathematical modeling techniques will extend its use into multi-dimensional modeling, introducing new variables and increasing the modeling accuracy. We propose a model: melting/solidification-model (M/S-model) - predicting the solute profile at the start of the solidification of a fusion weld. This Case 3-based Sub-Case takes into account the melting stage, the solute back-diffusion in the solid, and the growth rate acceleration typical to fusion welds. We propose - based on works of Rutter & Chalmers, David & Vitek and our experimental results on copper - that NEGS-EGS-transition is not associated only with cellular-dendritic-transition. Solidification is studied experimentally on pure and doped copper with welding speed range from 0 to 200 cm/min, with one test at 3000 cm/min. Found were only planar and cellular structures, no dendrites - columnar or equiaxed. Cell sub structures: rows of cubic elements we call "cubelettes", "cell-bands" and "micro-cells", as well as an anomalous crack morphology "crack-eye", were detected, as well as microscopic hot crack nucleus we call "grain-lag cracks", caused by a grain slightly lagging behind its neighbors in arrival to the weld centerline. Varestraint test and R-test revealed a change of crack morphologies from centerline cracks to grainand cell boundary cracks with an increasing welding speed. High speed made the cracks invisible to bare eye and hardly detectable with light microscope, while electron microscope often revealed networks of fine micro-cracks.

Um paradigma da química medicinal: a flexibilidade dos ligantes e receptores

In general, molecular modeling techniques applied in medicinal chemistry have been static and drug based. However the active site geometry and the intrinsic flexibility of both receptor and ligand are fundamental properties for molecular recognition and drug action. As a consequence, the use of dynamic models to describe the ligand-receptor complex is becoming a more common procedure. In this work we discuss the relevance of considering the receptor structure in medicinal chemistry studies as well as the flexibility of the ligand-receptor complex.

Liiketoimintaprosessien mittaaminen ja mallintaminen

Tutkimuksessa tutkitaan mallintamista ja mittaamista osana liiketoimintaproses-sien parantamista, sekä näiden asioiden kuvaamista soveltuvalla työkalulla. Ensin esitetään teoreettinen viitekehys siihen, kuinka prosesseja voidaan mitata ja mal-lintaa. Sitten raportoidaan käytännössä suoritettu kehitystyö, jolle on määritetty lähtö- ja tavoitetila. Työn onnistumista mitataan johtajahaastatteluin ja saatuja tuloksia verrataan teoriaan. Tutkimuksessa yhdistettiin analyyttinen mallinrakennus, tieteellinen ongelman-ratkaisutoiminta sekä konsultointi tarkoituksena saada aikaan kohde organisaati-olle sopiva konstruktio esitettyyn ongelmaan. Johtajahaastattelut analysoitiin ja suoritettiin kvalitatiivinen tarveanalyysi. Haastatteluja täydennettiin muulla kerä-tyllä aineistolla ja analyysin tarkkuutta pyritään kasvattamaan eri lähdeaineistojen ristivertailuilla. Yrityksissä on niin liiketoiminnalle elintärkeitä ydinprosesseja kuin niitä tukevia tukiprosessejakin. Niiden toiminta perustuu ennalta suunniteltuihin ja uudelleen-käytettäviin menetelmiin. Prosessit tulee sopeuttaa yrityksen arkkitehtuuriin ja niitä on jatkuvasti kehitettävä. Kehittäminen voidaan toteuttaa suurilla kertamuu-toksilla, jatkuvalla laadun parantamisella tai niiden yhdistelmänä. Mallintamisella ja mittaamisella on tärkeä tehtävä liiketoimintaprosessien kehit-tämisessä. Niiden avulla voidaan helpottaa erityisesti prosessien suunnittelua luomalla konkreettisia malleja ja mittareita prosesseista. Toteutuksessa käytettiin prototyyppilähestymistapaa ja työn onnistumista arvioivat yhtiön johtajat. Tutki-muksen tuloksia ovat eri tason prosessimallit, joiden luomisessa käytettiin eri mallintamistekniikoita, sekä mittaristot mittaamaan yrityksen tuottavuutta ja te-hokkuutta.

Conceptualizing and counteracting the bullying dynamic: Classroom and school contexts matter

Guided by the social-ecological conceptualization of bullying, this thesis examines the implications of classroom and school contexts—that is, students’ shared microsystems—for peer-to-peer bullying and antibullying practices. Included are four original publications, three of which are empirical studies utilizing data from a large Finnish sample of students in the upper grade levels of elementary school. Both self- and peer reports of bullying and victimization are utilized, and the hierarchical nature of the data collected from students nested within school ecologies is accounted for by multilevel modeling techniques. The first objective of the thesis is to simultaneously examine risk factors for victimization at individual, classroom, and school levels (Study I). The second objective is to uncover the individual- and classroom-level working mechanisms of the KiVa antibullying program which has been shown to be effective in reducing bullying problems in Finnish schools (Study II). Thirdly, an overview of the extant literature on classroom- and school-level contributions to bullying and victimization is provided (Study III). Finally, attention is paid to the assessment of victimization and, more specifically, to how the classroom context influences the concordance between self- and peer reports of victimization (Study IV). Findings demonstrate the multiple ways in which contextual factors, and importantly students’ perceptions thereof, contribute to the bullying dynamic and efforts to counteract it. Whereas certain popular beliefs regarding the implications of classroom and school contexts do not receive support, the role of peer contextual factors and the significance of students’ perceptions of teachers’ attitudes toward bullying are highlighted. Directions for future research and school-based antibullying practices are suggested.