A maximum likelihood algorithm for genome mapping of cytogenetic loci from meiotic configuration data.

Frequencies of meiotic configurations in cytogenetic stocks are dependent on chiasma frequencies in segments defined by centromeres, breakpoints, and telomeres. The expectation maximization algorithm is proposed as a general method to perform maximum likelihood estimations of the chiasma frequencies in the intervals between such locations. The estimates can be translated via mapping functions into genetic maps of cytogenetic landmarks. One set of observational data was analyzed to exemplify application of these methods, results of which were largely concordant with other comparable data. The method was also tested by Monte Carlo simulation of frequencies of meiotic configurations from a monotelodisomic translocation heterozygote, assuming six different sample sizes. The estimate averages were always close to the values given initially to the parameters. The maximum likelihood estimation procedures can be extended readily to other kinds of cytogenetic stocks and allow the pooling of diverse cytogenetic data to collectively estimate lengths of segments, arms, and chromosomes.

Two Consistent Many-Valued Logics for Paraconsistent Phenomena

In this reviewing paper, we recall the main results of our papers [24, 31] where we introduced two paraconsistent semantics for Pavelka style fuzzy logic. Each logic formula a is associated with a 2 x 2 matrix called evidence matrix. The two semantics are consistent if they are seen from 'outside'; the structure of the set of the evidence matrices M is an MV-algebra and there is nothing paraconsistent there. However, seen from "inside,' that is, in the construction of a single evidence matrix paraconsistency comes in, truth and falsehood are not each others complements and there is also contradiction and lack of information (unknown) involved. Moreover, we discuss the possible applications of the two logics in real-world phenomena.

Truth Values in t-norm based Systems Many-valued FUZZY Logic

In t-norm based systems many-valued logic, valuations of propositions form a non-countable set: interval [0,1]. In addition, we are given a set E of truth values p, subject to certain conditions, the valuation v is v=V(p), V reciprocal application of E on [0,1]. The general propositional algebra of t-norm based many-valued logic is then constructed from seven axioms. It contains classical logic (not many-valued) as a special case. It is first applied to the case where E=[0,1] and V is the identity. The result is a t-norm based many-valued logic in which contradiction can have a nonzero degree of truth but cannot be true; for this reason, this logic is called quasi-paraconsistent.

Supporting Access to Finance by SMEs: Mapping the initiatives in five EU countries. ECMI Research Report No. 9, April 2014

This paper maps the initiatives to support access to finance for small- and medium-sized enterprises (SMEs) that were available at national level in 2012 in the five biggest European economies (Germany, France, the UK, Italy and Spain). This mapping distinguishes initiatives promoted and financed primarily through public resources from those developed independently by the market. A second breakdown is proposed for those sources of finance with different targets, i.e. whether the target is debt financing (typically bank loans at favourable conditions, public guarantees on loans, etc.) or equity financing (typically venture capital funds, tax incentives on equity investments, etc.). A broad set of initiatives has been implemented to close the funding gap of SMEs in these five countries. The total amount of public spending for SMEs, however, has remained well below 1% of GDP. Public subsidisation of bank loans has been by far the most diffused type of intervention. Despite the fact that this strategy might prove to be effective in the short term, it fails to address long-term sustainability issues via a more diversified set of financing tools.

Mapping Emotion Terms into Affective Space: Further Evidence for a Four-Dimensional Structure

Recent empirical work on the semantics of emotion terms across many different cultures and languages, using a theoretical componential approach, suggested that four dimensions are needed to parsimoniously describe the semantic space of the emotion domain as reflected in emotion terms (Fontaine, Scherer, Roesch, & Ellsworth, 2007; Fontaine, Scherer, & Soriano, 2013). In addition to valence, power, and arousal, a novelty dimension was discovered that mostly differentiated surprise from other emotions. Here, we further explore the existence and nature of the fourth dimension in semantic emotion space using a much larger and much more representative set of emotion terms. A group of 156 participants each rated 10 out of a set of 80 French emotion terms with respect to semantic meaning. The meaning of an emotion term was evaluated with respect to 68 emotion features representing the appraisal, action tendency, bodily reaction, expression, and feeling components of the emotion process. A principal component analysis confirmed the four-dimensional valence, power, arousal, and novelty structure. Moreover, this larger and much more representative set of emotion terms revealed that the novelty dimension not only differentiates surprise terms from other emotion terms, but also identifies substantial variation within the fear and joy emotion families.

Fine mapping of the tomato I-3 gene for fusarium wilt resistance and elimination of a co-segregating resistance gene analogue as a candidate for I-3

The I-3 gene from the wild tomato species Lycopersicon pennellii confers resistance to race 3 of the devastating vascular wilt pathogen Fusarium oxysporum f. sp. lycopersici. As an initial step in a positional cloning strategy for the isolation of I-3, we converted restriction fragment length polymorphism and conserved orthologue set markers, known genes and a resistance gene analogue (RGA) mapping to the I-3 region into PCR-based sequence characterised amplified region (SCAR) and cleaved amplified polymorphic sequence (CAPS) markers. Additional PCR-based markers in the I-3 region were generated using the randomly amplified DNA fingerprinting (RAF) technique. SCAR, CAPS and RAF markers were used for high-resolution mapping around the I-3 locus. The I-3 gene was localised to a 0.3-cM region containing a RAF marker, eO6, and an RGA, RGA332. RGA332 was cloned and found to correspond to a putative pseudogene with at least two loss-of-function mutations. The predicted pseudogene belongs to the Toll interleukin-1 receptor-nucleotide-binding site-leucine-rich-repeat sub-class of plant disease resistance genes. Despite the presence of two RGA332 homologues in L. esculentum, DNA gel blot and PCR analysis suggests that no other homologues are present in lines carrying I-3 that could be alternative candidates for the gene.

Evaluation of unsupervised semantic mapping of natural language with Leximancer concept mapping

The Leximancer system is a relatively new method for transforming lexical co-occurrence information from natural language into semantic patterns in an unsupervised manner. It employs two stages of co-occurrence information extraction-semantic and relational-using a different algorithm for each stage. The algorithms used are statistical, but they employ nonlinear dynamics and machine learning. This article is an attempt to validate the output of Leximancer, using a set of evaluation criteria taken from content analysis that are appropriate for knowledge discovery tasks.

Biologically inspired visual landmark processing for simultaneous localization and mapping

This paper illustrates a method for finding useful visual landmarks for performing simultaneous localization and mapping (SLAM). The method is based loosely on biological principles, using layers of filtering and pooling to create learned templates that correspond to different views of the environment. Rather than using a set of landmarks and reporting range and bearing to the landmark, this system maps views to poses. The challenge is to produce a system that produces the same view for small changes in robot pose, but provides different views for larger changes in pose. The method has been developed to interface with the RatSLAM system, a biologically inspired method of SLAM. The paper describes the method of learning and recalling visual landmarks in detail, and shows the performance of the visual system in real robot tests.

Mapping civil society in former Yugoslavia

From the break up of the New Left into single issue groups at the end of the 1960s came a variety of groups representing the peace movement, environmental movement, student movement, women’s movement, and gay liberation movement. This explosion of new social movement activism has been heralded as the age of new radical politics. Many theorists and activists understand new social movements, as replacing the working class as an agent for progressive social change. Scholars and activists now alike debate the possibilities for revolutionary change in this era of multinational capitalism and new nationalisms. This paper examines some of the above claims in the context of the contemporary Serbian civil society. It explores the relationship between the civil society, activism, and narratives in Serbia. In particular, it examines the anti-Milosevic’ movement Otpor! (Resistance), and its discourse, practice and politics in public spaces, through an analysis of narratives of a set of roughly 20 interviews with Otpor! activists, aged 18-35. In the following discussion, then, I will focus on some of the particular dilemmas of contemporary Serbian popular movements - they are dilemmas to do with the growing complexity of media life in the Serbian spaces. I ground my debate on particular uses of the notion of civil society in the narratives of Otpor! activists, while I focus on the question of how do Otpor! activists relate to Leftist/radical politics and the idea of civil society.

Multi-valued control problems and mixture density network

We have proposed a novel robust inversion-based neurocontroller that searches for the optimal control law by sampling from the estimated Gaussian distribution of the inverse plant model. However, for problems involving the prediction of continuous variables, a Gaussian model approximation provides only a very limited description of the properties of the inverse model. This is usually the case for problems in which the mapping to be learned is multi-valued or involves hysteritic transfer characteristics. This often arises in the solution of inverse plant models. In order to obtain a complete description of the inverse model, a more general multicomponent distributions must be modeled. In this paper we test whether our proposed sampling approach can be used when considering an arbitrary conditional probability distributions. These arbitrary distributions will be modeled by a mixture density network. Importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The effectiveness of the importance sampling from an arbitrary conditional probability distribution will be demonstrated using a simple single input single output static nonlinear system with hysteretic characteristics in the inverse plant model.

Outlier detection with partial information:Application to emergency mapping

This paper, addresses the problem of novelty detection in the case that the observed data is a mixture of a known 'background' process contaminated with an unknown other process, which generates the outliers, or novel observations. The framework we describe here is quite general, employing univariate classification with incomplete information, based on knowledge of the distribution (the 'probability density function', 'pdf') of the data generated by the 'background' process. The relative proportion of this 'background' component (the 'prior' 'background' 'probability), the 'pdf' and the 'prior' probabilities of all other components are all assumed unknown. The main contribution is a new classification scheme that identifies the maximum proportion of observed data following the known 'background' distribution. The method exploits the Kolmogorov-Smirnov test to estimate the proportions, and afterwards data are Bayes optimally separated. Results, demonstrated with synthetic data, show that this approach can produce more reliable results than a standard novelty detection scheme. The classification algorithm is then applied to the problem of identifying outliers in the SIC2004 data set, in order to detect the radioactive release simulated in the 'oker' data set. We propose this method as a reliable means of novelty detection in the emergency situation which can also be used to identify outliers prior to the application of a more general automatic mapping algorithm. © Springer-Verlag 2007.

Strategic HRM through the cultural looking glass:mapping the cognition of British and Indian managers

This study examines the issues of `integration' of human resource management (HRM) into the corporate strategy, `devolvement' of HRM to line managers and the perceived influence of national culture on HRM in a cross-national comparative context. In order to achieve this, the cognition of personnel specialists from a matched sample of 48 Indian and British firms in the manufacturing sector using the `Visual Cards Sorting' and `CMAP2' methodologies are analyzed. The findings show that even where there is an apparent convergence of strategy — e.g., the desire of both Indian and British personnel managers to increase integration between HRM and business strategy, and to increase the level of devolvement to line managers, the two sets of specialists clearly follow a different logic of action, which is subject to a different set of cross-cultural influences. The implications of pursuing apparently similar HRM solutions in different cross-national contexts are considered. The analysis shows that HRM strategies, when considered in a cross-national context, vary a lot. Different logic leads to the adoption of similar HR strategies, and similar strategies in turn are perceived as producing different outcomes. This variance centres around the existence and perceived influence of several contextual variables such as industrial relations systems, operation of labour markets, and changes in business systems. Specific cross-cultural influences, along with different aspects of competitive business environment associated with the generic HR strategies of integration and devolvement in the two countries are highlighted. This research contributes to the fields of cross-cultural management research, international HRM and managerial and organizational cognition. It also has important messages for policy makers.

Constructing localized non-linear projection manifolds in a principled way:hierarchical generative topographic mapping

It has been argued that a single two-dimensional visualization plot may not be sufficient to capture all of the interesting aspects of complex data sets, and therefore a hierarchical visualization system is desirable. In this paper we extend an existing locally linear hierarchical visualization system PhiVis (Bishop98a) in several directions: 1. We allow for em non-linear projection manifolds. The basic building block is the Generative Topographic Mapping. 2. We introduce a general formulation of hierarchical probabilistic models consisting of local probabilistic models organized in a hierarchical tree. General training equations are derived, regardless of the position of the model in the tree. 3. Using tools from differential geometry we derive expressions for local directionalcurvatures of the projection manifold. Like PhiVis, our system is statistically principled and is built interactively in a top-down fashion using the EM algorithm. It enables the user to interactively highlight those data in the parent visualization plot which are captured by a child model.We also incorporate into our system a hierarchical, locally selective representation of magnification factors and directional curvatures of the projection manifolds. Such information is important for further refinement of the hierarchical visualization plot, as well as for controlling the amount of regularization imposed on the local models. We demonstrate the principle of the approach on a toy data set andapply our system to two more complex 12- and 19-dimensional data sets.

An integer-valued data envelopment analysis model with bounded outputs

Integer-valued data envelopment analysis (DEA) with alternative returns to scale technology has been introduced and developed recently by Kuosmanen and Kazemi Matin. The proportionality assumption of their introduced "natural augmentability" axiom in constant and nondecreasing returns to scale technologies makes it possible to achieve feasible decision-making units (DMUs) of arbitrary large size. In many real world applications it is not possible to achieve such production plans since some of the input and output variables are bounded above. In this paper, we extend the axiomatic foundation of integer-valuedDEAmodels for including bounded output variables. Some model variants are achieved by introducing a new axiom of "boundedness" over the selected output variables. A mixed integer linear programming (MILP) formulation is also introduced for computing efficiency scores in the associated production set. © 2011 The Authors. International Transactions in Operational Research © 2011 International Federation of Operational Research Societies.

An Algorithmic Approach to Inferring Cross-Ontology Links while Mapping Anatomical Ontologies

ACM Computing Classification System (1998): J.3.