Molecular phylogenetics and temporal diversification in the genus Aeromonas based on the sequences of five housekeeping genes

Several approaches have been developed to estimate both the relative and absolute rates of speciation and extinction within clades based on molecular phylogenetic reconstructions of evolutionary relationships, according to an underlying model of diversification. However, the macroevolutionary models established for eukaryotes have scarcely been used with prokaryotes. We have investigated the rate and pattern of cladogenesis in the genus Aeromonas (γ-Proteobacteria, Proteobacteria, Bacteria) using the sequences of five housekeeping genes and an uncorrelated relaxed-clock approach. To our knowledge, until now this analysis has never been applied to all the species described in a bacterial genus and thus opens up the possibility of establishing models of speciation from sequence data commonly used in phylogenetic studies of prokaryotes. Our results suggest that the genus Aeromonas began to diverge between 248 and 266 million years ago, exhibiting a constant divergence rate through the Phanerozoic, which could be described as a pure birth process.

Classical line shapes based on analytical solutions of bimolecular trajectories in collision induced emission. II. Reactive collisions

The classical theory of collision induced emission (CIE) from pairs of dissimilar rare gas atoms was developed in Paper I [D. Reguera and G. Birnbaum, J. Chem. Phys. 125, 184304 (2006)] from a knowledge of the straight line collision trajectory and the assumption that the magnitude of the dipole could be represented by an exponential function of the inter-nuclear distance. This theory is extended here to deal with other functional forms of the induced dipole as revealed by ab initio calculations. Accurate analytical expression for the CIE can be obtained by least square fitting of the ab initio values of the dipole as a function of inter-atomic separation using a sum of exponentials and then proceeding as in Paper I. However, we also show how the multi-exponential fit can be replaced by a simpler fit using only two analytic functions. Our analysis is applied to the polar molecules HF and HBr. Unlike the rare gas atoms considered previously, these atomic pairs form stable bound diatomic molecules. We show that, interestingly, the spectra of these reactive molecules are characterized by the presence of multiple peaks. We also discuss the CIE arising from half collisions in excited electronic states, which in principle could be probed in photo-dissociation experiments.

Adjusting for the environment in DEA: a comparison of alternative models based on empirical data

Due to the existence of free software and pedagogical guides, the use of Data Envelopment Analysis (DEA) has been further democratized in recent years. Nowadays, it is quite usual for practitioners and decision makers with no or little knowledge in operational research to run their own efficiency analysis. Within DEA, several alternative models allow for an environmental adjustment. Four alternative models, each user-friendly and easily accessible to practitioners and decision makers, are performed using empirical data of 90 primary schools in the State of Geneva, Switzerland. Results show that the majority of alternative models deliver divergent results. From a political and a managerial standpoint, these diverging results could lead to potentially ineffective decisions. As no consensus emerges on the best model to use, practitioners and decision makers may be tempted to select the model that is right for them, in other words, the model that best reflects their own preferences. Further studies should investigate how an appropriate multi-criteria decision analysis method could help decision makers to select the right model.

From Regional Landslide Detection to Site-Specific Slope Deformation Monitoring and Modelling Based on Active Remote Sensors

Landslide processes can have direct and indirect consequences affecting human lives and activities. In order to improve landslide risk management procedures, this PhD thesis aims to investigate capabilities of active LiDAR and RaDAR sensors for landslides detection and characterization at regional scales, spatial risk assessment over large areas and slope instabilities monitoring and modelling at site-specific scales. At regional scales, we first demonstrated recent boat-based mobile LiDAR capabilities to model topography of the Normand coastal cliffs. By comparing annual acquisitions, we validated as well our approach to detect surface changes and thus map rock collapses, landslides and toe erosions affecting the shoreline at a county scale. Then, we applied a spaceborne InSAR approach to detect large slope instabilities in Argentina. Based on both phase and amplitude RaDAR signals, we extracted decisive information to detect, characterize and monitor two unknown extremely slow landslides, and to quantify water level variations of an involved close dam reservoir. Finally, advanced investigations on fragmental rockfall risk assessment were conducted along roads of the Val de Bagnes, by improving approaches of the Slope Angle Distribution and the FlowR software. Therefore, both rock-mass-failure susceptibilities and relative frequencies of block propagations were assessed and rockfall hazard and risk maps could be established at the valley scale. At slope-specific scales, in the Swiss Alps, we first integrated ground-based InSAR and terrestrial LiDAR acquisitions to map, monitor and model the Perraire rock slope deformation. By interpreting both methods individually and originally integrated as well, we therefore delimited the rockslide borders, computed volumes and highlighted non-uniform translational displacements along a wedge failure surface. Finally, we studied specific requirements and practical issues experimented on early warning systems of some of the most studied landslides worldwide. As a result, we highlighted valuable key recommendations to design new reliable systems; in addition, we also underlined conceptual issues that must be solved to improve current procedures. To sum up, the diversity of experimented situations brought an extensive experience that revealed the potential and limitations of both methods and highlighted as well the necessity of their complementary and integrated uses.

Dry months in the agricultural region of Ribeirão Preto, state of São Paulo-Brazil: an study based on the extreme value theory

The application of the Extreme Value Theory (EVT) to model the probability of occurrence of extreme low Standardized Precipitation Index (SPI) values leads to an increase of the knowledge related to the occurrence of extreme dry months. This sort of analysis can be carried out by means of two approaches: the block maxima (BM; associated with the General Extreme Value distribution) and the peaks-over-threshold (POT; associated with the Generalized Pareto distribution). Each of these procedures has its own advantages and drawbacks. Thus, the main goal of this study is to compare the performance of BM and POT in characterizing the probability of occurrence of extreme dry SPI values obtained from the weather station of Ribeirão Preto-SP (1937-2012). According to the goodness-of-fit tests, both BM and POT can be used to assess the probability of occurrence of the aforementioned extreme dry SPI monthly values. However, the scalar measures of accuracy and the return level plots indicate that POT provides the best fit distribution. The study also indicated that the uncertainties in the parameters estimates of a probabilistic model should be taken into account when the probability associated with a severe/extreme dry event is under analysis.

Strategic Innovation Management Based on Three Dimensions

This thesis examines innovation development needs of firms in a remote rural region. The perspective of the study is in strategic innovation management and three dimensions of innovation development: innovation environment, value delivery and innovation capability. The framework is studied with a theoretical and methodological approach in the context of the development of a regional innovation system and the defining of innovation development needs. The thesis is based on existing innovation management literature, expanding it by examining the features of the three dimensions. The empirical data of the study comprise 50 purposefully selected firms within the region of Pielinen Karelia located in Eastern Finland. Most of the firms (70%) included in the study represent manufacturing firms, and over 90% are small and medium-sized enterprises. The research data consist of two questionnaires and an interview, which were done during 2011 in the connection of a regional development project. The point of view of the research is in regional development and harnessing the innovation capability of the firms within the region. The principal research approach applies soft systems methodology. The study explores the means to foster the innovativeness of firms from the viewpoints of innovation environment, innovation capability and value delivery. In closer detail, the study examines relations between the innovation capability factors, differences in innovation development needs within the value delivery system, between sectors and between firm size categories. The thesis offers three major contributions. First, the study extends earlier research on strategic innovation management by connecting the frameworks of innovation capability, innovation environment and value delivery process to the defining of innovation development needs at the regional level. The results deepen knowledge especially concerning practice-based innovation, peripheral regions and smaller firms. Second, the empirical work, based on a case study, confirms the existence of a structural connection integrating five factors of innovation capability. Statistical evidence is provided especially for the positive impacts of the improvement of absorption capability, marketing capability and networking capability, which are the main weaknesses of firms according to the study. Third, the research provides a methodological contribution by applying the innovation matrix in the defining of the innovation development needs of firms. The study demonstrates how the matrix improves possibility to target policy instruments and innovation services more efficiently through indicating significant differences between the innovation support needs regarding various time horizons and phases of innovation process.

Modelling the simultaneous effects of intellectual capital and knowledge management on the organisational performance of Finnish companies

The aim of this study was to contribute to the current knowledge-based theory by focusing on a research gap that exists in the empirically proven determination of the simultaneous but differentiable effects of intellectual capital (IC) assets and knowledge management (KM) practices on organisational performance (OP). The analysis was built on the past research and theoreticised interactions between the latent constructs specified using the survey-based items that were measured from a sample of Finnish companies for IC and KM and the dependent construct for OP determined using information available from financial databases. Two widely used and commonly recommended measures in the literature on management science, i.e. the return on total assets (ROA) and the return on equity (ROE), were calculated for OP. Thus the investigation of the relationship between IC and KM impacting OP in relation to the hypotheses founded was possible to conduct using objectively derived performance indicators. Using financial OP measures also strengthened the dynamic features of data needed in analysing simultaneous and causal dependences between the modelled constructs specified using structural path models. The estimates were obtained for the parameters of structural path models using a partial least squares-based regression estimator. Results showed that the path dependencies between IC and OP or KM and OP were always insignificant when analysed separate to any other interactions or indirect effects caused by simultaneous modelling and regardless of the OP measure used that was either ROA or ROE. The dependency between the constructs for KM and IC appeared to be very strong and was always significant when modelled simultaneously with other possible interactions between the constructs and using either ROA or ROE to define OP. This study, however, did not find statistically unambiguous evidence for proving the hypothesised causal mediation effects suggesting, for instance, that the effects of KM practices on OP are mediated by the IC assets. Due to the fact that some indication about the fluctuations of causal effects was assessed, it was concluded that further studies are needed for verifying the fundamental and likely hidden causal effects between the constructs of interest. Therefore, it was also recommended that complementary modelling and data processing measures be conducted for elucidating whether the mediation effects occur between IC, KM and OP, the verification of which requires further investigations of measured items and can be build on the findings of this study.

Perception of privacy in smartphone applications: profiling users based on personality types.

This document is focused on studying privacy perception and personality traits of users in the context of smartphone application privacy. It is divided into two parts. The first part presents an in depth systematic literature review of the existing academic writings available on the topic of relation between privacy perception and personality traits. Demographics, methodologies and other useful insight is extracted and the available literature is divided into broader group of topics bringing the five main areas of research to light and highlighting the current research trends in the field along with pinpointing the research gap of interest to the author. The second part of the thesis uses the results from the literature review to administer an empirical study to investigate the current privacy perception of users and the correlation between personality traits and privacy perception in smartphone applications. Big five personality test is used as the measure for personality traits whereas three sub-variables are used to measure privacy perception i.e. perceived privacy awareness, perceived threat to privacy and willingness to trade privacy. According to the study openness to experience is the most dominant trait having a strong correlation with two privacy sub-variables whereas emotional stability doesn’t show any correlation with privacy perception. Empirical study also explores other findings as preferred privacy sources and application installation preferences that provide further insight about users and might be useful in future.

GA approach for finding Rough Set decision rules based on bireducts

Feature selection plays an important role in knowledge discovery and data mining nowadays. In traditional rough set theory, feature selection using reduct - the minimal discerning set of attributes - is an important area. Nevertheless, the original definition of a reduct is restrictive, so in one of the previous research it was proposed to take into account not only the horizontal reduction of information by feature selection, but also a vertical reduction considering suitable subsets of the original set of objects. Following the work mentioned above, a new approach to generate bireducts using a multi--objective genetic algorithm was proposed. Although the genetic algorithms were used to calculate reduct in some previous works, we did not find any work where genetic algorithms were adopted to calculate bireducts. Compared to the works done before in this area, the proposed method has less randomness in generating bireducts. The genetic algorithm system estimated a quality of each bireduct by values of two objective functions as evolution progresses, so consequently a set of bireducts with optimized values of these objectives was obtained. Different fitness evaluation methods and genetic operators, such as crossover and mutation, were applied and the prediction accuracies were compared. Five datasets were used to test the proposed method and two datasets were used to perform a comparison study. Statistical analysis using the one-way ANOVA test was performed to determine the significant difference between the results. The experiment showed that the proposed method was able to reduce the number of bireducts necessary in order to receive a good prediction accuracy. Also, the influence of different genetic operators and fitness evaluation strategies on the prediction accuracy was analyzed. It was shown that the prediction accuracies of the proposed method are comparable with the best results in machine learning literature, and some of them outperformed it.

Towards a new Qur’ânic hermeneutics based on historico-critical and intertextual approaches : the case of the crucifixion of Jesus in the tafâsîr of eight muslim exegetes

Le Coran et la Sunna (la tradition du prophète Muḥammad) relatée dans les aḥâdîth (les traditions orales du Prophète) représentent la source éternelle d’inspiration et de savoir à laquelle les Musulmans se réfèrent pour agir, réagir et interagir. Par le fait même, tout au long de l’histoire musulmane, ces sources sacrées ont été à la base des relations des Musulmans avec autrui, incluant les Chrétiens. Les trois éléments majeurs de différenciation entre l’islam et le christianisme sont : la nature divine de Jésus, la trinité ainsi que la crucifixion et la mort de Jésus sur la croix. La position tranchée du Coran quant aux deux premiers points ne laisse place à aucun débat académique. Cependant, l’ambiguïté du texte coranique quant à la crucifixion de Jésus et sa mort a favorisé de nombreux débats entre mufassirûn (les exégètes du Coran). Cette thèse est une analyse textuelle des deux passages coraniques qui traitent de cette troisième différence. Pour cette étude textuelle et intertextuelle, les tafâsîr (interprétations du Coran) de huit mufassirûn appartenant à différentes madhâhib (écoles d’interprétation) et périodes de l’histoire des relations musulmanes-chrétiennes sont utilisés en combinaison avec certaines approches et méthodes récentes telles que : historico-critique et critique rédactionnelle. De plus, trois nouvelles théories développées dans la thèse enrichissent les outils herméneutiques de la recherche : la « théorie des cinq couches de sens », la « théorie des messages coraniques doubles » et la « théorie de la nature humaine tripartite ». À la lumière de ces théories et méthodes, il apparaît que l’ambiguïté coranique au sujet de la crucifixion et de la mort de Jésus est une invitation claire de la part du Coran incitant les Musulmans et les Chrétiens à vivre avec cette ambiguïté insoluble. La conclusion de cette thèse contribue directement à de meilleures relations musulmanes-chrétiennes, renforçant l’appel coranique (Coran 3:64, 103) à ces deux communautés leurs demandant de se cramponner aux points communs majeurs, d’intégrer leurs différences mineures et de consacrer leurs énergies pour une vie harmonieuse entre eux et laisser le reste dans les mains du Dieu qu’ils ont en commun.

Analysis and Testing of a Novel Oadm Based on FBG and Machzehnder Interferometer

A novel optical add-drop multiplexer (OADM) based on the Mach-Zelauler interferometer (MZI) and the fiber Bragg grating (FBG) is proposed for the first tittle to the authors ' knowledge. In the structure, the Mach-Zehnder interferometer acts as an optical switch. The principle of the OADM is analyzed in this paper. The OADM can add/drop one of the multi-input channels or pass the channel directly by adjusting the difference of the two arms of the interferometer. The channel isolation is more than 20 dB

k-NN based On-Line Handwritten Character recognition system

On-line handwriting recognition has been a frontier area of research for the last few decades under the purview of pattern recognition. Word processing turns to be a vexing experience even if it is with the assistance of an alphanumeric keyboard in Indian languages. A natural solution for this problem is offered through online character recognition. There is abundant literature on the handwriting recognition of western, Chinese and Japanese scripts, but there are very few related to the recognition of Indic script such as Malayalam. This paper presents an efficient Online Handwritten character Recognition System for Malayalam Characters (OHR-M) using K-NN algorithm. It would help in recognizing Malayalam text entered using pen-like devices. A novel feature extraction method, a combination of time domain features and dynamic representation of writing direction along with its curvature is used for recognizing Malayalam characters. This writer independent system gives an excellent accuracy of 98.125% with recognition time of 15-30 milliseconds

Design of a Knowledge-Based Geographic Information System

A GIS has been designed with limited Functionalities; but with a novel approach in Aits design. The spatial data model adopted in the design of KBGIS is the unlinked vector model. Each map entity is encoded separately in vector fonn, without referencing any of its neighbouring entities. Spatial relations, in other words, are not encoded. This approach is adequate for routine analysis of geographic data represented on a planar map, and their display (Pages 105-106). Even though spatial relations are not encoded explicitly, they can be extracted through the specially designed queries. This work was undertaken as an experiment to study the feasibility of developing a GIS using a knowledge base in place of a relational database. The source of input spatial data was accurate sheet maps that were manually digitised. Each identifiable geographic primitive was represented as a distinct object, with its spatial properties and attributes defined. Composite spatial objects, made up of primitive objects, were formulated, based on production rules defining such compositions. The facts and rules were then organised into a production system, using OPS5

Efficient data mining based on formal concept analysis

Formal Concept Analysis is an unsupervised learning technique for conceptual clustering. We introduce the notion of iceberg concept lattices and show their use in Knowledge Discovery in Databases (KDD). Iceberg lattices are designed for analyzing very large databases. In particular they serve as a condensed representation of frequent patterns as known from association rule mining. In order to show the interplay between Formal Concept Analysis and association rule mining, we discuss the algorithm TITANIC. We show that iceberg concept lattices are a starting point for computing condensed sets of association rules without loss of information, and are a visualization method for the resulting rules.

Efficient mining of association rules based on formal concept analysis

Association rules are a popular knowledge discovery technique for warehouse basket analysis. They indicate which items of the warehouse are frequently bought together. The problem of association rule mining has first been stated in 1993. Five years later, several research groups discovered that this problem has a strong connection to Formal Concept Analysis (FCA). In this survey, we will first introduce some basic ideas of this connection along a specific algorithm, TITANIC, and show how FCA helps in reducing the number of resulting rules without loss of information, before giving a general overview over the history and state of the art of applying FCA for association rule mining.