Diversifying selection and color-biased dispersal in the asp viper.

BACKGROUND: The presence of intraspecific color polymorphism can have multiple impacts on the ecology of a species; as a consequence, particular color morphs may be strongly selected for in a given habitat type. For example, the asp viper (Vipera aspis) shows a high level of color polymorphism. A blotched morph (cryptic) is common throughout its range (central and western Europe), while a melanistic morph is frequently found in montane populations, presumably for thermoregulatory reasons. Besides, rare atypical uniformly colored individuals are known here and there. Nevertheless, we found in a restricted treeless area of the French Alps, a population containing a high proportion (>50%) of such specimens. The aim of the study is to bring insight into the presence and function of this color morph by (i) studying the genetic structure of these populations using nine microsatellite markers, and testing for (ii) a potential local diversifying selection and (iii) differences in dispersal capacity between blotched and non-blotched vipers. RESULTS: Our genetic analyses support the occurrence of local diversifying selection for the non-blotched phenotype. In addition, we found significant color-biased dispersal, blotched individuals dispersing more than atypical individuals. CONCLUSION: We hypothesize that, in this population, the non-blotched phenotype possess an advantage over the typical one, a phenomenon possibly due to a better background matching ability in a more open habitat. In addition, color-biased dispersal might be partly associated with the observed local diversifying selection, as it can affect the genetic structure of populations, and hence the distribution of color morphs.

Using species richness and functional traits predictions to constrain assemblage predictions from stacked species distribution models

Aim: Modelling species at the assemblage level is required to make effective forecast of global change impacts on diversity and ecosystem functioning. Community predictions may be achieved using macroecological properties of communities (MEM), or by stacking of individual species distribution models (S-SDMs). To obtain more realistic predictions of species assemblages, the SESAM framework suggests applying successive filters to the initial species source pool, by combining different modelling approaches and rules. Here we provide a first test of this framework in mountain grassland communities. Location: The western Swiss Alps. Methods: Two implementations of the SESAM framework were tested: a "Probability ranking" rule based on species richness predictions and rough probabilities from SDMs, and a "Trait range" rule that uses the predicted upper and lower bound of community-level distribution of three different functional traits (vegetative height, specific leaf area and seed mass) to constraint a pool of environmentally filtered species from binary SDMs predictions. Results: We showed that all independent constraints expectedly contributed to reduce species richness overprediction. Only the "Probability ranking" rule allowed slightly but significantly improving predictions of community composition. Main conclusion: We tested various ways to implement the SESAM framework by integrating macroecological constraints into S-SDM predictions, and report one that is able to improve compositional predictions. We discuss possible improvements, such as further improving the causality and precision of environmental predictors, using other assembly rules and testing other types of ecological or functional constraints.

Selecting, testing and modifying a model for identifying potential key customers

Tämä työ tehtiin globaaliin elektroniikka-alan yritykseen. Diplomityö liittyy haasteeseen, jonka lisääntynyt globalisaatio ja kiristyvä kilpailu ovat luoneet: case yrityksen on selvitettävä kuinka se voi saavuttaa kasvutavoitteet myös tulevaisuudessa hankkimalla uusia asiakkaita ja olemalla yhä enenevissä määrin maailmanlaajuisesti läsnä. Tutkimuksen tavoite oli löytää sopiva malli potentiaalisten avainasiakkaiden identifiointiin ja valintaan, sekä testata ja modifioida valittua mallia case yrityksen tarpeiden mukaisesti. Erityisesti raakadatan kerääminen, asiakkaiden houkuttelevuuskriteerit ja kohdemarkkinarako olivat asioita, jotka tarvitsivat tutkimuksessa huomiota. Kirjallisuuskatsauksessa keskityttiin yritysmarkkinoihin, eri asiakassuhteenhallinnan lähestymistapoihin ja avainasiakkaiden määrittämiseen. CRM:n, KAM:n ja Customer Insight-ajattelun perusteet esiteltiin yhdessä eri avainasiakkaiden identifiointimallien kanssa. Valittua Chevertonin mallia testattiin ja muokattiin työn empiirisessä osassa. Tutkimuksen empiirinen kontribuutio on modifioitu malli potentiaalisten avainasiakkaiden identifiointiin. Se auttaa päätöksentekijöitä etenemään systemaattisesti ja organisoidusti askel askeleelta kohti potentiaalisten asiakkaiden listaa tietyltä markkina-alueelta. Työ tarjoaa työkalun tähän prosessiin sekä luo pohjaa tulevaisuuden tutkimukselle ja toimenpiteille.

Classification and inventory management of abnormal demand items

The main objective of the study is to form a framework that provides tools to recognise and classify items whose demand is not smooth but varies highly on size and/or frequency. The framework will then be combined with two other classification methods in order to form a three-dimensional classification model. Forecasting and inventory control of these abnormal demand items is difficult. Therefore another object of this study is to find out which statistical forecasting method is most suitable for forecasting of abnormal demand items. The accuracy of different methods is measured by comparing the forecast to the actual demand. Moreover, the study also aims at finding proper alternatives to the inventory control of abnormal demand items. The study is quantitative and the methodology is a case study. The research methods consist of theory, numerical data, current state analysis and testing of the framework in case company. The results of the study show that the framework makes it possible to recognise and classify the abnormal demand items. It is also noticed that the inventory performance of abnormal demand items differs significantly from the performance of smoothly demanded items. This makes the recognition of abnormal demand items very important.

Reuse of information for selection of methods and operating conditions for drying of pharmaceutical materials

Drying is a major step in the manufacturing process in pharmaceutical industries, and the selection of dryer and operating conditions are sometimes a bottleneck. In spite of difficulties, the bottlenecks are taken care of with utmost care due to good manufacturing practices (GMP) and industries' image in the global market. The purpose of this work is to research the use of existing knowledge for the selection of dryer and its operating conditions for drying of pharmaceutical materials with the help of methods like case-based reasoning and decision trees to reduce time and expenditure for research. The work consisted of two major parts as follows: Literature survey on the theories of spray dying, case-based reasoning and decision trees; working part includes data acquisition and testing of the models based on existing and upgraded data. Testing resulted in a combination of two models, case-based reasoning and decision trees, leading to more specific results when compared to conventional methods.

Improving anterior deltoid activity in a musculoskeletal shoulder model - an analysis of the torque-feasible space at the sternoclavicular joint.

Modelling the shoulder's musculature is challenging given its mechanical and geometric complexity. The use of the ideal fibre model to represent a muscle's line of action cannot always faithfully represent the mechanical effect of each muscle, leading to considerable differences between model-estimated and in vivo measured muscle activity. While the musculo-tendon force coordination problem has been extensively analysed in terms of the cost function, only few works have investigated the existence and sensitivity of solutions to fibre topology. The goal of this paper is to present an analysis of the solution set using the concepts of torque-feasible space (TFS) and wrench-feasible space (WFS) from cable-driven robotics. A shoulder model is presented and a simple musculo-tendon force coordination problem is defined. The ideal fibre model for representing muscles is reviewed and the TFS and WFS are defined, leading to the necessary and sufficient conditions for the existence of a solution. The shoulder model's TFS is analysed to explain the lack of anterior deltoid (DLTa) activity. Based on the analysis, a modification of the model's muscle fibre geometry is proposed. The performance with and without the modification is assessed by solving the musculo-tendon force coordination problem for quasi-static abduction in the scapular plane. After the proposed modification, the DLTa reaches 20% of activation.

Dustiness and deagglomeration testing: interlaboratory comparison of systems for nanoparticle powders

Different types of aerosolization and deagglomeration testing systems exist for studying the properties of nanomaterial powders and their aerosols. However, results are dependent on the specific methods used. In order to have well-characterized aerosols, we require a better understanding of how system parameters and testing conditions influence the properties of the aerosols generated. In the present study, four experimental setups delivering different aerosolization energies were used to test the resultant aerosols of two distinct nanomaterials (hydrophobic and hydrophilic TiO2). The reproducibility of results within each system was good. However, the number concentrations and size distributions of the aerosols created varied across the four systems; for number concentrations, e.g., from 10(3) to 10(6) #/cm(3). Moreover, distinct differences were also observed between the two materials with different surface coatings. The article discusses how system characteristics and other pertinent conditions modify the test results. We propose using air velocity as a suitable proxy for estimating energy input levels in aerosolization systems. The information derived from this work will be especially useful for establishing standard operating procedures for testing nanopowders, as well as for estimating their release rates under different energy input conditions, which is relevant for occupational exposure.

Patient-centered Care in Maternity Services: A Critical Appraisal and Synthesis of the Literature.

BACKGROUND: Patient-centered care (PCC) has been recognized as a marker of quality in health service delivery. In policy documents, PCC is often used interchangeably with other models of care. There is a wide literature about PCC, but there is a lack of evidence about which model is the most appropriate for maternity services specifically. AIM: We sought to identify and critically appraise the literature to identify which definition of PCC is most relevant for maternity services. METHODS: The four-step approach used to identify definitions of PCC was to 1) search electronic databases using key terms (1995-2011), 2) cross-reference key papers, 3) search of specific journals, and 4) search the grey literature. Four papers and two books met our inclusion criteria. ANALYSIS: A four-criteria critical appraisal tool developed for the review was used to appraise the papers and books. MAIN RESULTS: From the six identified definitions, the Shaller's definition met the majority of the four criteria outlined and seems to be the most relevant to maternity services because it includes physiologic conditions as well as pathology, psychological aspects, a nonmedical approach to care, the greater involvement of family and friends, and strategies to implement PCC. CONCLUSION: This review highlights Shaller's definitions of PCC as the one that would be the most inclusive of all women using maternity services. Future research should concentrate on evaluating programs that support PCC in maternity services, and testing/validating this model of care.

Analysis of space-time environmental data in complex regions

This thesis develops a comprehensive and a flexible statistical framework for the analysis and detection of space, time and space-time clusters of environmental point data. The developed clustering methods were applied in both simulated datasets and real-world environmental phenomena; however, only the cases of forest fires in Canton of Ticino (Switzerland) and in Portugal are expounded in this document. Normally, environmental phenomena can be modelled as stochastic point processes where each event, e.g. the forest fire ignition point, is characterised by its spatial location and occurrence in time. Additionally, information such as burned area, ignition causes, landuse, topographic, climatic and meteorological features, etc., can also be used to characterise the studied phenomenon. Thereby, the space-time pattern characterisa- tion represents a powerful tool to understand the distribution and behaviour of the events and their correlation with underlying processes, for instance, socio-economic, environmental and meteorological factors. Consequently, we propose a methodology based on the adaptation and application of statistical and fractal point process measures for both global (e.g. the Morisita Index, the Box-counting fractal method, the multifractal formalism and the Ripley's K-function) and local (e.g. Scan Statistics) analysis. Many measures describing the space-time distribution of environmental phenomena have been proposed in a wide variety of disciplines; nevertheless, most of these measures are of global character and do not consider complex spatial constraints, high variability and multivariate nature of the events. Therefore, we proposed an statistical framework that takes into account the complexities of the geographical space, where phenomena take place, by introducing the Validity Domain concept and carrying out clustering analyses in data with different constrained geographical spaces, hence, assessing the relative degree of clustering of the real distribution. Moreover, exclusively to the forest fire case, this research proposes two new methodologies to defining and mapping both the Wildland-Urban Interface (WUI) described as the interaction zone between burnable vegetation and anthropogenic infrastructures, and the prediction of fire ignition susceptibility. In this regard, the main objective of this Thesis was to carry out a basic statistical/- geospatial research with a strong application part to analyse and to describe complex phenomena as well as to overcome unsolved methodological problems in the characterisation of space-time patterns, in particular, the forest fire occurrences. Thus, this Thesis provides a response to the increasing demand for both environmental monitoring and management tools for the assessment of natural and anthropogenic hazards and risks, sustainable development, retrospective success analysis, etc. The major contributions of this work were presented at national and international conferences and published in 5 scientific journals. National and international collaborations were also established and successfully accomplished. -- Cette thèse développe une méthodologie statistique complète et flexible pour l'analyse et la détection des structures spatiales, temporelles et spatio-temporelles de données environnementales représentées comme de semis de points. Les méthodes ici développées ont été appliquées aux jeux de données simulées autant qu'A des phénomènes environnementaux réels; nonobstant, seulement le cas des feux forestiers dans le Canton du Tessin (la Suisse) et celui de Portugal sont expliqués dans ce document. Normalement, les phénomènes environnementaux peuvent être modélisés comme des processus ponctuels stochastiques ou chaque événement, par ex. les point d'ignition des feux forestiers, est déterminé par son emplacement spatial et son occurrence dans le temps. De plus, des informations tels que la surface bru^lée, les causes d'ignition, l'utilisation du sol, les caractéristiques topographiques, climatiques et météorologiques, etc., peuvent aussi être utilisées pour caractériser le phénomène étudié. Par conséquent, la définition de la structure spatio-temporelle représente un outil puissant pour compren- dre la distribution du phénomène et sa corrélation avec des processus sous-jacents tels que les facteurs socio-économiques, environnementaux et météorologiques. De ce fait, nous proposons une méthodologie basée sur l'adaptation et l'application de mesures statistiques et fractales des processus ponctuels d'analyse global (par ex. l'indice de Morisita, la dimension fractale par comptage de boîtes, le formalisme multifractal et la fonction K de Ripley) et local (par ex. la statistique de scan). Des nombreuses mesures décrivant les structures spatio-temporelles de phénomènes environnementaux peuvent être trouvées dans la littérature. Néanmoins, la plupart de ces mesures sont de caractère global et ne considèrent pas de contraintes spatiales com- plexes, ainsi que la haute variabilité et la nature multivariée des événements. A cet effet, la méthodologie ici proposée prend en compte les complexités de l'espace géographique ou le phénomène a lieu, à travers de l'introduction du concept de Domaine de Validité et l'application des mesures d'analyse spatiale dans des données en présentant différentes contraintes géographiques. Cela permet l'évaluation du degré relatif d'agrégation spatiale/temporelle des structures du phénomène observé. En plus, exclusif au cas de feux forestiers, cette recherche propose aussi deux nouvelles méthodologies pour la définition et la cartographie des zones périurbaines, décrites comme des espaces anthropogéniques à proximité de la végétation sauvage ou de la forêt, et de la prédiction de la susceptibilité à l'ignition de feu. A cet égard, l'objectif principal de cette Thèse a été d'effectuer une recherche statistique/géospatiale avec une forte application dans des cas réels, pour analyser et décrire des phénomènes environnementaux complexes aussi bien que surmonter des problèmes méthodologiques non résolus relatifs à la caractérisation des structures spatio-temporelles, particulièrement, celles des occurrences de feux forestières. Ainsi, cette Thèse fournit une réponse à la demande croissante de la gestion et du monitoring environnemental pour le déploiement d'outils d'évaluation des risques et des dangers naturels et anthro- pogéniques. Les majeures contributions de ce travail ont été présentées aux conférences nationales et internationales, et ont été aussi publiées dans 5 revues internationales avec comité de lecture. Des collaborations nationales et internationales ont été aussi établies et accomplies avec succès.

Change points detection in crime-related time series: an on-line fuzzy approach based on a shape space representation

The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables is particularly useful in crime analysis, where intuitive, understandable, and appropriate detection of changes can significantly improve the allocation of resources for timely and concise operations. In this paper, we propose an on-line method for detecting and querying change points in crime-related time series with the use of a meaningful representation and a fuzzy inference system. Change points detection is based on a shape space representation, and linguistic terms describing geometric properties of the change points are used to express queries, offering the advantage of intuitiveness and flexibility. An empirical evaluation is first conducted on a crime data set to confirm the validity of the proposed method and then on a financial data set to test its general applicability. A comparison to a similar change-point detection algorithm and a sensitivity analysis are also conducted. Results show that the method is able to accurately detect change points at very low computational costs. More broadly, the detection of specific change points within time series of virtually any domain is made more intuitive and more understandable, even for experts not related to data mining.

Determining risk potential through accidents and near-accidents: an empirical study in a steel factory

Fatal and permanently disabling accidents form only one per I cent of all occupational accidents but in many branches of industry they account for more than half the accident costs. Furthermore the human suffering of the victim and his family is greater in severe accidents than in slight ones. For both human and economic reasons the severe accident risks should be identified befor injuries occur. It is for this purpose that different safety analysis methods have been developed . This study shows two new possible approaches to the problem.. The first is the hypothesis that it is possible to estimate the potential severity of accidents independent of the actual severity. The second is the hypothesis that when workers are also asked to report near accidents, they are particularly prone to report potentially severe near accidents on the basis of their own subjective risk assessment. A field study was carried out in a steel factory. The results supported both the hypotheses. The reliability and the validity of post incident estimates of an accident's potential severity were reasonable. About 10 % of accidents were estimated to be potentially critical; they could have led to death or very severe permanent disability. Reported near accidents were significantly more severe, about 60 $ of them were estimated to be critical. Furthermore the validity of workers subjective risk assessment, manifested in the near accident reports, proved to be reasonable. The studied new methods require further development and testing. They could be used both in routine usage in work places and in research for identifying and setting the priorities of accident risks.

Introducing Continuous Integration for C and C++ Software Development Projects on Linux Platform

Software integration is a stage in a software development process to assemble separate components to produce a single product. It is important to manage the risks involved and being able to integrate smoothly, because software cannot be released without integrating it first. Furthermore, it has been shown that the integration and testing phase can make up 40 % of the overall project costs. These issues can be mitigated by using a software engineering practice called continuous integration. This thesis work presents how continuous integration is introduced to the author's employer organisation. This includes studying how the continuous integration process works and creating the technical basis to start using the process on future projects. The implemented system supports software written in C and C++ programming languages on Linux platform, but the general concepts can be applied to any programming language and platform by selecting the appropriate tools. The results demonstrate in detail what issues need to be solved when the process is acquired in a corporate environment. Additionally, they provide an implementation and process description suitable to the organisation. The results show that continuous integration can reduce the risks involved in a software process and increase the quality of the product as well.

A Survey and Classification of Software Testing Tools

Software testing is one of the essential parts in software engineering process. The objective of the study was to describe software testing tools and the corresponding use. The thesis contains examples of software testing tools usage. The study was conducted as a literature study, with focus on current software testing practices and quality assurance standards. In the paper a tool classifier was employed, and testing tools presented in study were classified according to it. We found that it is difficult to distinguish current available tools by certain testing activities as many of them contain functionality that exceeds scopes of a single testing type.

Environmental inFluences on the Adoption of Open Innovation: Analysis of Structural, Institutional and Cultural Impacts

The concept of open innovation has recently gained widespread attention, and is particularly relevant now as many firms endeavouring to implement open innovation, face different sets of challenges associated with managing it. Prior research on open innovation has focused on the internal processes dealing with open innovation implementation and the organizational changes, already taking place or yet required in companies order to succeed in the global open innovation market. Despite the intensive research on open innovation, the question of what influences its adoption by companies in different contexts has not received much attention in studies. To fill this gap, this thesis contribute to the discussion on open innovation influencing factors by bringing in the perspective of environmental impacts, i.e. gathering data on possible sources of external influences, classifying them and testing their systemic impact through conceptual system dynamics simulation model. The insights from data collection and conceptualization in modelling are used to answer the question of how the external environment affects the adoption of open innovation. The thesis research is presented through five research papers reflecting the method triangulation based study (conducted at initial stage as case study, later as quantitative analysis and finally as system dynamics simulation). This multitude of methods was used to collect the possible external influence factors and to assess their impact (on positive/negative scale rather than numerical). The results obtained throughout the thesis research bring valuable insights into understanding of open innovation influencing factors inside a firm’s operating environment, point out the balance required in the system for successful open innovation performance and discover the existence of tipping point of open innovation success when driven by market dynamics and structures. The practical implications on how firms and policy-makers can leverage environment for their potential benefits are offered in the conclusions.

Modelling of combustion and sorbent reactions in three-dimensional flow environment of a circulating fluidized bed furnace

This thesis presents a three-dimensional, semi-empirical, steady state model for simulating the combustion, gasification, and formation of emissions in circulating fluidized bed (CFB) processes. In a large-scale CFB furnace, the local feeding of fuel, air, and other input materials, as well as the limited mixing rate of different reactants produce inhomogeneous process conditions. To simulate the real conditions, the furnace should be modelled three-dimensionally or the three-dimensional effects should be taken into account. The only available methods for simulating the large CFB furnaces three-dimensionally are semi-empirical models, which apply a relatively coarse calculation mesh and a combination of fundamental conservation equations, theoretical models and empirical correlations. The number of such models is extremely small. The main objective of this work was to achieve a model which can be applied to calculating industrial scale CFB boilers and which can simulate all the essential sub-phenomena: fluid dynamics, reactions, the attrition of particles, and heat transfer. The core of the work was to develop the model frame and the required sub-models for determining the combustion and sorbent reactions. The objective was reached, and the developed model was successfully used for studying various industrial scale CFB boilers combusting different types of fuel. The model for sorbent reactions, which includes the main reactions for calcitic limestones, was applied for studying the new possible phenomena occurring in the oxygen-fired combustion. The presented combustion and sorbent models and principles can be utilized in other model approaches as well, including other empirical and semi-empirical model approaches, and CFD based simulations. The main achievement is the overall model frame which can be utilized for the further development and testing of new sub-models and theories, and for concentrating the knowledge gathered from the experimental work carried out at bench scale, pilot scale and industrial scale apparatus, and from the computational work performed by other modelling methods.