Comparing skew Schur functions: a quasisymmetric perspective

Reiner, Shaw and van Willigenburg showed that if two skew Schur functions sA and sB are equal, then the skew shapes $A$ and $B$ must have the same "row overlap partitions." Here we show that these row overlap equalities are also implied by a much weaker condition than Schur equality: that sA and sB have the same support when expanded in the fundamental quasisymmetric basis F. Surprisingly, there is significant evidence supporting a conjecture that the converse is also true. In fact, we work in terms of inequalities, showing that if the F-support of sA contains that of sB, then the row overlap partitions of A are dominated by those of B, and again conjecture that the converse also holds. Our evidence in favor of these conjectures includes their consistency with a complete determination of all F-support containment relations for F-multiplicity-free skew Schur functions. We conclude with a consideration of how some other quasisymmetric bases fit into our framework.

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

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

MODULARITY BASED FUZZY COMMUNITY DETECTION IN SOCIAL NETWORKS

Fuzzy community detection is to identify fuzzy communities in a network, which are groups of vertices in the network such that the membership of a vertex in one community is in [0,1] and that the sum of memberships of vertices in all communities equals to 1. Fuzzy communities are pervasive in social networks, but only a few works have been done for fuzzy community detection. Recently, a one-step forward extension of Newman’s Modularity, the most popular quality function for disjoint community detection, results into the Generalized Modularity (GM) that demonstrates good performance in finding well-known fuzzy communities. Thus, GMis chosen as the quality function in our research. We first propose a generalized fuzzy t-norm modularity to investigate the effect of different fuzzy intersection operators on fuzzy community detection, since the introduction of a fuzzy intersection operation is made feasible by GM. The experimental results show that the Yager operator with a proper parameter value performs better than the product operator in revealing community structure. Then, we focus on how to find optimal fuzzy communities in a network by directly maximizing GM, which we call it Fuzzy Modularity Maximization (FMM) problem. The effort on FMM problem results into the major contribution of this thesis, an efficient and effective GM-based fuzzy community detection method that could automatically discover a fuzzy partition of a network when it is appropriate, which is much better than fuzzy partitions found by existing fuzzy community detection methods, and a crisp partition of a network when appropriate, which is competitive with partitions resulted from the best disjoint community detections up to now. We address FMM problem by iteratively solving a sub-problem called One-Step Modularity Maximization (OSMM). We present two approaches for solving this iterative procedure: a tree-based global optimizer called Find Best Leaf Node (FBLN) and a heuristic-based local optimizer. The OSMM problem is based on a simplified quadratic knapsack problem that can be solved in linear time; thus, a solution of OSMM can be found in linear time. Since the OSMM algorithm is called within FBLN recursively and the structure of the search tree is non-deterministic, we can see that the FMM/FBLN algorithm runs in a time complexity of at least O (n2). So, we also propose several highly efficient and very effective heuristic algorithms namely FMM/H algorithms. We compared our proposed FMM/H algorithms with two state-of-the-art community detection methods, modified MULTICUT Spectral Fuzzy c-Means (MSFCM) and Genetic Algorithm with a Local Search strategy (GALS), on 10 real-world data sets. The experimental results suggest that the H2 variant of FMM/H is the best performing version. The H2 algorithm is very competitive with GALS in producing maximum modularity partitions and performs much better than MSFCM. On all the 10 data sets, H2 is also 2-3 orders of magnitude faster than GALS. Furthermore, by adopting a simply modified version of the H2 algorithm as a mutation operator, we designed a genetic algorithm for fuzzy community detection, namely GAFCD, where elite selection and early termination are applied. The crossover operator is designed to make GAFCD converge fast and to enhance GAFCD’s ability of jumping out of local minimums. Experimental results on all the data sets show that GAFCD uncovers better community structure than GALS.

Design and Impact of Awareness Functions – A Study about Social Media in Virtual Teams

The usage of social media in leisure time settings has become a prominent research topic. However, less research has been done on the design of social media in collaboration settings. In this study, we investigate how social media can support asynchronous collaboration in virtual teams and specifically how they can increase activity awareness. On the basis of an open source social networking platform, we present two prototype designs: a standard platform with basic support for information processing, communication and process – as suggested by Zigurs and Buckland (1998) – and an advanced platform with additional support for activity awareness via specialfeed functions. We argue that the standard platform already conveys activity awareness to a certain extent, however, that this awareness can be increased even more by the feeds in the advanced platform. Both prototypes are tested in a field experiment and evaluated with respect to their impact on perceived activity awareness, coordination and satisfaction. We show that the advanced design increases coordination and satisfaction through increased perceived activity awareness.

Quantitative 1H-magnetic resonance spectroscopy of human brain: Influence of composition and parameterization of the basis set in linear combination model-fitting

Localized short-echo-time (1)H-MR spectra of human brain contain contributions of many low-molecular-weight metabolites and baseline contributions of macromolecules. Two approaches to model such spectra are compared and the data acquisition sequence, optimized for reproducibility, is presented. Modeling relies on prior knowledge constraints and linear combination of metabolite spectra. Investigated was what can be gained by basis parameterization, i.e., description of basis spectra as sums of parametric lineshapes. Effects of basis composition and addition of experimentally measured macromolecular baselines were investigated also. Both fitting methods yielded quantitatively similar values, model deviations, error estimates, and reproducibility in the evaluation of 64 spectra of human gray and white matter from 40 subjects. Major advantages of parameterized basis functions are the possibilities to evaluate fitting parameters separately, to treat subgroup spectra as independent moieties, and to incorporate deviations from straightforward metabolite models. It was found that most of the 22 basis metabolites used may provide meaningful data when comparing patient cohorts. In individual spectra, sums of closely related metabolites are often more meaningful. Inclusion of a macromolecular basis component leads to relatively small, but significantly different tissue content for most metabolites. It provides a means to quantitate baseline contributions that may contain crucial clinical information.

A Restriction-Centered Theory of Reasoning and Computation to materialize a Web 3.0

Researchers suggest that personalization on the Semantic Web adds up to a Web 3.0 eventually. In this Web, personalized agents process and thus generate the biggest share of information rather than humans. In the sense of emergent semantics, which supplements traditional formal semantics of the Semantic Web, this is well conceivable. An emergent Semantic Web underlying fuzzy grassroots ontology can be accomplished through inducing knowledge from users' common parlance in mutual Web 2.0 interactions [1]. These ontologies can also be matched against existing Semantic Web ontologies, to create comprehensive top-level ontologies. On the Web, if augmented with information in the form of restrictions andassociated reliability (Z-numbers) [2], this collection of fuzzy ontologies constitutes an important basis for an implementation of Zadeh's restriction-centered theory of reasoning and computation (RRC) [3]. By considering real world's fuzziness, RRC differs from traditional approaches because it can handle restrictions described in natural language. A restriction is an answer to a question of the value of a variable such as the duration of an appointment. In addition to mathematically well-defined answers, RRC can likewise deal with unprecisiated answers as "about one hour." Inspired by mental functions, it constitutes an important basis to leverage present-day Web efforts to a natural Web 3.0. Based on natural language information, RRC may be accomplished with Z-number calculation to achieve a personalized Web reasoning and computation. Finally, through Web agents' understanding of natural language, they can react to humans more intuitively and thus generate and process information.

Molecular basis of Corynebacterium diphtheriae virulence and infection in the Caenorhabditis elegans model host

Corynebacterium diphtheriae is the causative agent of cutaneous and pharyngeal diphtheria in humans. While lethality is certainly caused by diphtheria toxin, corynebacterial colonization may primarily require proteinaceous fibers called pili, which mediate adherence to specific tissues. The type strain of C. diphtheriae possesses three distinct pilus structures, namely the SpaA, SpaD, and SpaH-type pili, which are encoded by three distinct pilus gene clusters. The pilus is assembled onto the bacterial peptidoglycan by a specific transpeptidase enzyme called sortase. Although the SpaA pili are shown to be specific for pharyngeal cells in vitro, little is known about functions of the three pili in bacterial pathogenesis. This is mainly due to lack of in vivo models of corynebacterial infection. As an alternative to mouse models as mice do not have functional receptors for diphtheria toxin, in this study I use Caenorhabditis elegans as a model host for C. diphtheriae. A simple C. elegans model would be beneficial in determining the specific role of each pilus-type and the literature suggests that C. elegans infection model can be used to study a variety of bacterial species giving insight into bacterial virulence and host-pathogen interactions. My study examines the hypothesis that pili and toxin are major virulent determinants of C. diphtheriae in the C. elegans model host.

Spectral bounds and basis results for non-self-adjoint pencils, with an application to Hagen-Poiseuille flow

We obtain eigenvalue enclosures and basisness results for eigen- and associated functions of a non-self-adjoint unbounded linear operator pencil A−λBA−λB in which BB is uniformly positive and the essential spectrum of the pencil is empty. Both Riesz basisness and Bari basisness results are obtained. The results are applied to a system of singular differential equations arising in the study of Hagen–Poiseuille flow with non-axisymmetric disturbances.

Adaptive fuzzy knowledge-based systems for control metabots' mobility on virtual environments

The confluence of three-dimensional (3D) virtual worlds with social networks imposes on software agents, in addition to conversational functions, the same behaviours as those common to human-driven avatars. In this paper, we explore the possibilities of the use of metabots (metaverse robots) with motion capabilities in complex virtual 3D worlds and we put forward a learning model based on the techniques used in evolutionary computation for optimizing the fuzzy controllers which will subsequently be used by metabots for moving around a virtual environment.

A recursive algorithm to compute a basis of a similarity

Se definen conceptos y se aplica el teorema de Valverde para escribir un algoritmo que computa bases de similaridades. This paper studies sorne theory and methods to build a representation theorem basis of a similarity from the basis of its subsimilarities, providing an alternative recursive method to compute the basis of a similarity.

Contribución al estudio de dos conceptos básicos de la lógica fuzzy

La tesis doctoral CONTRIBUCIÓN AL ESTUDIO DE DOS CONCEPTOS BÁSICOS DE LA LÓGICA FUZZY constituye un conjunto de nuevas aportaciones al análisis de dos elementos básicos de la lógica fuzzy: los mecanismos de inferencia y la representación de predicados vagos. La memoria se encuentra dividida en dos partes que corresponden a los dos aspectos señalados. En la Parte I se estudia el concepto básico de «estado lógico borroso». Un estado lógico borroso es un punto fijo de la aplicación generada a partir de la regla de inferencia conocida como modus ponens generalizado. Además, un preorden borroso puede ser representado mediante los preórdenes elementales generados por el conjunto de sus estados lógicos borrosos. El Capítulo 1 está dedicado a caracterizar cuándo dos estados lógicos dan lugar al mismo preorden elemental, obteniéndose también un representante de la clase de todos los estados lógicos que generan el mismo preorden elemental. El Capítulo finaliza con la caracterización del conjunto de estados lógicos borrosos de un preorden elemental. En el Capítulo 2 se obtiene un subconjunto borroso trapezoidal como una clase de una relación de indistinguibilidad. Finalmente, el Capítulo 3 se dedica a estudiar dos tipos de estados lógicos clásicos: los irreducibles y los minimales. En el Capítulo 4, que inicia la Parte II de la memoria, se aborda el problema de obtener la función de compatibilidad de un predicado vago. Se propone un método, basado en el conocimiento del uso del predicado mediante un conjunto de reglas y de ciertos elementos distinguidos, que permite obtener una expresión general de la función de pertenencia generalizada de un subconjunto borroso que realice la función de extensión del predicado borroso. Dicho método permite, en ciertos casos, definir un conjunto de conectivas multivaluadas asociadas al predicado. En el último capítulo se estudia la representación de antónimos y sinónimos en lógica fuzzy a través de auto-morfismos. Se caracterizan los automorfismos sobre el intervalo unidad cuando sobre él se consideran dos operaciones: una t-norma y una t-conorma ambas arquimedianas. The PhD Thesis CONTRIBUCIÓN AL ESTUDIO DE DOS CONCEPTOS BÁSICOS DE LA LÓGICA FUZZY is a contribution to two basic concepts of the Fuzzy Logic. It is divided in two parts, the first is devoted to a mechanism of inference in Fuzzy Logic, and the second to the representation of vague predicates. «Fuzzy Logic State» is the basic concept in Part I. A Fuzzy Logic State is a fixed-point for the mapping giving the Generalized Modus Ponens Rule of inference. Moreover, a fuzzy preordering can be represented by the elementary preorderings generated by its Fuzzy Logic States. Chapter 1 contemplates the identity of elementary preorderings and the selection of representatives for the classes modulo this identity. This chapter finishes with the characterization of the set of Fuzzy Logic States of an elementary preordering. In Chapter 2 a Trapezoidal Fuzzy Set as a class of a relation of Indistinguishability is obtained. Finally, Chapter 3 is devoted to study two types of Classical Logic States: irreducible and minimal. Part II begins with Chapter 4 dealing with the problem of obtaining a Compa¬tibility Function for a vague predicate. When the use of a predicate is known by means of a set of rules and some distinguished elements, a method to obtain the general expression of the Membership Function is presented. This method allows, in some cases, to reach a set of multivalued connectives associated to the predicate. Last Chapter is devoted to the representation of antonyms and synonyms in Fuzzy Logic. When the unit interval [0,1] is endowed with both an archimedean t-norm and a an archi-medean t-conorm, it is showed that the automorphisms' group is just reduced to the identity function.

Obtaining contradiction measure on intuitionistic fuzzy sets from fuzzy connectives

In a previous paper, we proposed an axiomatic model for measuring self-contradiction in the framework of Atanassov fuzzy sets. This way, contradiction measures that are semicontinuous and completely semicontinuous, from both below and above, were defined. Although some examples were given, the problem of finding families of functions satisfying the different axioms remained open. The purpose of this paper is to construct some families of contradiction measures firstly using continuous t-norms and t-conorms, and secondly by means of strong negations. In both cases, we study the properties that they satisfy. These families are then classified according the different kinds of measures presented in the above paper.

About t-norms on type-2 fuzzy sets.

Walker et al. defined two families of binary operations on M (set of functions of [0,1] in [0,1]), and they determined that, under certain conditions, those operations are t-norms (triangular norm) or t-conorms on L (all the normal and convex functions of M). We define binary operations on M, more general than those given by Walker et al., and we study many properties of these general operations that allow us to deduce new t-norms and t-conorms on both L, and M.

Tool wear monitoring using neuro-fuzzy techniques: a comparative study in a turning process

Tool wear detection is a key issue for tool condition monitoring. The maximization of useful tool life is frequently related with the optimization of machining processes. This paper presents two model-based approaches for tool wear monitoring on the basis of neuro-fuzzy techniques. The use of a neuro-fuzzy hybridization to design a tool wear monitoring system is aiming at exploiting the synergy of neural networks and fuzzy logic, by combining human reasoning with learning and connectionist structure. The turning process that is a well-known machining process is selected for this case study. A four-input (i.e., time, cutting forces, vibrations and acoustic emissions signals) single-output (tool wear rate) model is designed and implemented on the basis of three neuro-fuzzy approaches (inductive, transductive and evolving neuro-fuzzy systems). The tool wear model is then used for monitoring the turning process. The comparative study demonstrates that the transductive neuro-fuzzy model provides better error-based performance indices for detecting tool wear than the inductive neuro-fuzzy model and than the evolving neuro-fuzzy model.

Molecular basis of salt tolerance in Physcomitrella Patens model plant: potassium homeostasis and physiological roles of chx transporters

El suelo salino impone un estrés abiótico importante que causa graves problemas en la agricultura ya que la mayoría de los cultivos se ven afectados por la salinidad debido a efectos osmóticos y tóxicos. Por ello, la contaminación y la escasez de agua dulce, la salinización progresiva de tierras y el aumento exponencial de la población humana representan un grave problema que amenaza la seguridad alimentaria mundial para las generaciones futuras. Por lo tanto, aumentar la tolerancia a la salinidad de los cultivos es un objetivo estratégico e ineludible para garantizar el suministro de alimentos en el futuro. Mantener una óptima homeostasis de K+ en plantas que sufren estrés salino es un objetivo importante en el proceso de obtención de plantas tolerantes a la salinidad. Aunque el modelo de la homeostasis de K+ en las plantas está razonablemente bien descrito en términos de entrada de K+, muy poco se sabe acerca de los genes implicados en la salida de K+ o de su liberación desde la vacuola. En este trabajo se pretende aclarar algunos de los mecanismos implicados en la homeostasis de K+ en plantas. Para ello se eligió la briofita Physcomitrella patens, una planta no vascular de estructura simple y de fase haploide dominante que, entre muchas otras cualidades, hacen que sea un modelo ideal. Lo más importante es que no sólo P. patens es muy tolerante a altas concentraciones de Na+, sino que también su posición filogenética en la evolución de las plantas abre la posibilidad de estudiar los cambios claves que, durante el curso de la evolución, se produjeron en las diversas familias de los transportadores de K+. Se han propuesto varios transportadores de cationes como candidatos que podrían tener un papel en la salida de K+ o su liberación desde la vacuola, especialmente miembros de la familia CPA2 que contienen las familias de transportadores KEA y CHX. En este estudio se intenta aumentar nuestra comprensión de las funciones de los transportadores de CHX en las células de las plantas usando P. patens, como ya se ha dicho. En esta especie, se han identificado cuatro genes CHX, PpCHX1-4. Dos de estos genes, PpCHX1 y PpCHX2, se expresan aproximadamente al mismo nivel que el gen PpACT5, y los otros dos genes muestran una expresión muy baja. La expresión de PpCHX1 y PpCHX2 en mutantes de Escherichia coli defectivos en el transporte de K+ restauraron el crecimiento de esta cepa en medios con bajo contenido de K+, lo que viii sugiere que la entrada de K+ es energizada por un mecanismo de simporte con H+. Por otra parte, estos transportadores suprimieron el defecto asociado a la mutación kha1 en Saccharomyces cerevisiae, lo que sugiere que podrían mediar un antiporte en K+/H+. La proteína PpCHX1-GFP expresada transitoriamente en protoplastos de P. patens co-localizó con un marcador de Golgi. En experimentos similares, la proteína PpCHX2-GFP localizó aparentemente en la membrana plasmática y tonoplasto. Se construyeron las líneas mutantes simples de P. patens ΔPpchx1 y ΔPpchx2, y también el mutante doble ΔPpchx2 ΔPphak1. Los mutantes simples crecieron normalmente en todas las condiciones ensayadas y mostraron flujos de entrada normales de K+ y Rb+; la mutación ΔPpchx2 no aumentó el defecto de las plantas ΔPphak1. En experimentos a largo plazo, las plantas ΔPpchx2 mostraron una retención de Rb+ ligeramente superior que las plantas silvestres, lo que sugiere que PpCHX2 promueve la transferencia de Rb+ desde la vacuola al citosol o desde el citosol al medio externo, actuando en paralelo con otros transportadores. Sugerimos que transportadores de K+ de varias familias están involucrados en la homeostasis de pH de orgánulos ya sea mediante antiporte K+/H+ o simporte K+-H+.ix ABSTRACT Soil salinity is a major abiotic stress causing serious problems in agriculture as most crops are affected by it. Moreover, the contamination and shortage of freshwater, progressive land salinization and exponential increase of human population aggravates the problem implying that world food security may not be ensured for the next generations. Thus, a strategic and an unavoidable goal would be increasing salinity tolerance of plant crops to secure future food supply. Maintaining an optimum K+ homeostasis in plants under salinity stress is an important trait to pursue in the process of engineering salt tolerant plants. Although the model of K+ homeostasis in plants is reasonably well described in terms of K+ influx, very little is known about the genes implicated in K+ efflux or release from the vacuole. In this work, we aim to clarify some of the mechanisms involved in K+ homeostasis in plants. For this purpose, we chose the bryophyte plant Physcomitrella patens, a nonvascular plant of simple structure and dominant haploid phase that, among many other characteristics, makes it an ideal model. Most importantly, not only P. patens is very tolerant to high concentrations of Na+, but also its phylogenetic position in land plant evolution opens the possibility to study the key changes that occurred in K+ transporter families during the course of evolution. Several cation transporter candidates have been proposed to have a role in K+ efflux or release from the vacuole especially members of the CPA2 family which contains the KEA and CHX transporter families. We intended in this study to increase our understanding of the functions of CHX transporters in plant cells using P. patens, in which four CHX genes have been identified, PpCHX1-4. Two of these genes, PpCHX1 and PpCHX2, are expressed at approximately the same level as the PpACT5 gene, but the other two genes show an extremely low expression. PpCHX1 and PpCHX2 restored growth of Escherichia coli mutants on low K+-containing media, suggesting they mediated K+ uptake that may be energized by symport with H+. In contrast, these genes suppressed the defect associated to the kha1 mutation in Saccharomyces cerevisiae, which suggest that they might mediate K+/H+ antiport. PpCHX1-GFP protein transiently expressed in P. patens protoplasts co-localized with a Golgi marker. In similar experiments, the PpCHX2-GFP protein appeared to localize to tonoplast and plasma x membrane. We constructed the ΔPpchx1 and ΔPpchx2 single mutant lines, and the ΔPpchx2 ΔPphak1 double mutant. Single mutant plants grew normally under all the conditions tested and exhibited normal K+ and Rb+ influxes; the ΔPpchx2 mutation did not increase the defect of ΔPphak1 plants. In long-term experiments, ΔPpchx2 plants showed a slightly higher Rb+ retention than wild type plants, which suggests that PpCHX2 mediates the transfer of Rb+ from either the vacuole to the cytosol or from the cytosol to the external medium in parallel with other transporters. We suggest that K+ transporters of several families are involved in the pH homeostasis of organelles by mediating either K+/H+ antiport or K+-H+ symport.