Combinatorial interaction between AtbZIP44 and other bZIP transcription factors in the regulation of Arabidopsis thaliana seed maturation and germination

El gen AtbZIP44 se expresa en el endospermo micropilar y en la radícula de semillas en germinación. El mRNA del gen AtbZIP9 se localiza también en la radícula. Se realizan experimentos de interacción proteína-proteína entre los correspondientes factores transcripcionales.

Auxin - oxylipin crosstalk in stress responses of plant roots

Phytohormones regulate a wide array of developmental processes throughout the life cycle of plants. Over recent years, mounting evidence led to the widely accepted concept that plant hormone action is not the read-out of linear pathways, but determined by the extensive combinatorial activity of the signaling molecules and the integration of their signaling pathways, both in terms of regulating growth and development and in adapting to external stimuli. Recent work is beginning to shed light on the crosstalk of both nominally synergistically and antagonistically acting plant hormones such as, for example, auxins with oxylipins. Here, we report that oxylipins directly contribute to the regulation of the expression of two Arabidopsis YUCCA (YUC) genes, YUC8 and YUC9. Similar to previously characterized YUC family members, we identify both YUC8 and YUC9 as involved in local auxin biosynthesis, as demonstrated by the altered auxin contents and auxin-dependent phenotypes displayed by loss-of function mutants and transgenic overexpressing lines. Gene expression data obtained by qPCR analysis and microscopic examination of promoter-reporter lines reveal an oxylipin-mediated regulation of YUC9 expression that is dependent on the COI1 signal transduction pathway. The microscopic data indicate a functional overlap of the two analyzed auxin biosynthesis genes, but also point out specific functions for YUC8 and YUC9, which are in part related to different spatio-temporal expression pattern. In support of these findings, the analyzed yuc knockout mutants had lower free auxin contents and displayed a reduced response to oxylipins. This work provides evidence of a molecular mechanism that links oxylipin signaling with auxin homeostasis.

CP debugging needs and tools

Conventional programming techniques are not well suited for solving many highly combinatorial industrial problems, like scheduling, decision making, resource allocation or planning. Constraint Programming (CP), an emerging software technology, offers an original approach allowing for efficient and flexible solving of complex problems, through combined implementation of various constraint solvers and expert heuristics. Its applications are increasingly elded in various industries.

Phase transition in the countdown problem

We present a combinatorial decision problem, inspired by the celebrated quiz show called Countdown, that involves the computation of a given target number T from a set of k randomly chosen integers along with a set of arithmetic operations. We find that the probability of winning the game evidences a threshold phenomenon that can be understood in the terms of an algorithmic phase transition as a function of the set size k. Numerical simulations show that such probability sharply transitions from zero to one at some critical value of the control parameter, hence separating the algorithm's parameter space in different phases. We also find that the system is maximally efficient close to the critical point. We derive analytical expressions that match the numerical results for finite size and permit us to extrapolate the behavior in the thermodynamic limit.

Cross-entropy optimization for scaling factors of a fuzzy controller: a see-and-avoid approach for unmanned aerial systems

The Cross-Entropy (CE) is an efficient method for the estimation of rare-event probabilities and combinatorial optimization. This work presents a novel approach of the CE for optimization of a Soft-Computing controller. A Fuzzy controller was designed to command an unmanned aerial system (UAS) for avoiding collision task. The only sensor used to accomplish this task was a forward camera. The CE is used to reach a near-optimal controller by modifying the scaling factors of the controller inputs. The optimization was realized using the ROS-Gazebo simulation system. In order to evaluate the optimization a big amount of tests were carried out with a real quadcopter.

Solving the minimum vertex floodlight problem with hybrid metaheuristics

In this paper we propose four approximation algorithms (metaheuristic based), for the Minimum Vertex Floodlight Set problem. Urrutia et al. [9] solved the combinatorial problem, although it is strongly believed that the algorithmic problem is NP-hard. We conclude that, on average, the minimum number of vertex floodlights needed to illuminate a orthogonal polygon with n vertices is n/4,29.

Quantity and degree assessment in an RDF.based semantic language

This paper introduces a semantic language developed with the objective to be used in a semantic analyzer based on linguistic and world knowledge. Linguistic knowledge is provided by a Combinatorial Dictionary and several sets of rules. Extra-linguistic information is stored in an Ontology. The meaning of the text is represented by means of a series of RDF-type triples of the form predicate (subject, object). Semantic analyzer is one of the options of the multifunctional ETAP-3 linguistic processor. The analyzer can be used for Information Extraction and Question Answering. We describe semantic representation of expressions that provide an assessment of the number of objects involved and/or give a quantitative evaluation of different types of attributes. We focus on the following aspects: 1) parametric and non-parametric attributes; 2) gradable and non-gradable attributes; 3) ontological representation of different classes of attributes; 4) absolute and relative quantitative assessment; 5) punctual and interval quantitative assessment; 6) intervals with precise and fuzzy boundaries

Robustness and Recoverability in Transport Logistics

Abstract Transport is the foundation of any economy: it boosts economic growth, creates wealth, enhances trade, geographical accessibility and the mobility of people. Transport is also a key ingredient for a high quality of life, making places accessible and bringing people together. The future prosperity of our world will depend on the ability of all of its regions to remain fully and competitively integrated in the world economy. Efficient transport is vital in making this happen. Operations research can help in efficiently planning the design and operating transport systems. Planning and operational processes are fields that are rich in combinatorial optimization problems. These problems can be analyzed and solved through the application of mathematical models and optimization techniques, which may lead to an improvement in the performance of the transport system, as well as to a reduction in the time required for solving these problems. The latter aspect is important, because it increases the flexibility of the system: the system can adapt in a faster way to changes in the environment (i.e.: weather conditions, crew illness, failures, etc.). These disturbing changes (called disruptions) often enforce the schedule to be adapted. The direct consequences are delays and cancellations, implying many schedule adjustments and huge costs. Consequently, robust schedules and recovery plans must be developed in order to fight against disruptions. This dissertation makes contributions to two different fields: rail and air applications. Robust planning and recovery methods are presented. In the field of railway transport we develop several mathematical models which answer to RENFE’s (the major railway operator in Spain) needs: 1. We study the rolling stock assignment problem: here, we introduce some robust aspects in order to ameliorate some operations which are likely to fail. Once the rolling stock assignment is known, we propose a robust routing model which aims at identifying the train units’ sequences while minimizing the expected delays and human resources needed to perform the sequences. 2. It is widely accepted that the sequential solving approach produces solutions that are not global optima. Therefore, we develop an integrated and robust model to determine the train schedule and rolling stock assignment. We also propose an integrated model to study the rolling stock circulations. Circulations are determined by the rolling stock assignment and routing of the train units. 3. Although our aim is to develop robust plans, disruptions will be likely to occur and recovery methods will be needed. Therefore, we propose a recovery method which aims to recover the train schedule and rolling stock assignment in an integrated fashion all while considering the passenger demand. In the field of air transport we develop several mathematical models which answer to IBERIA’s (the major airline in Spain) needs: 1. We look at the airline-scheduling problem and develop an integrated approach that optimizes schedule design, fleet assignment and passenger use so as to reduce costs and create fewer incompatibilities between decisions. Robust itineraries are created to ameliorate misconnected passengers. 2. Air transport operators are continuously facing competition from other air operators and different modes of transport (e.g., High Speed Rail). Consequently, airline profitability is critically influenced by the airline’s ability to estimate passenger demands and construct profitable flight schedules. We consider multi-modal competition including airline and rail, and develop a new approach that estimates the demand associated with a given schedule; and generates airline schedules and fleet assignments using an integrated schedule design and fleet assignment optimization model that captures the impacts of schedule decisions on passenger demand.

Homogeneous links and the Seifert matrix

Homogeneous links were introduced by Peter Cromwell, who pr oved that the projection surface of these links, that given by the Seifert al- gorithm, has minimal genus. Here we provide a different proof , with a geometric rather than combinatorial flavor. To do this, we fir st show a direct relation between the Seifert matrix and the decompo sition into blocks of the Seifert graph. Precisely, we prove that the Sei fert matrix can be arranged in a block triangular form, with small boxes in th e diagonal corresponding to the blocks of the Seifert graph. Then we pro ve that the boxes in the diagonal has non-zero determinant, by looking a t an explicit matrix of degrees given by the planar structure of the Seifer t graph. The paper contains also a complete classification of the homogen eous knots of genus one.

Approximate Relational Reasoning for Probabilistic Programs

La seguridad verificada es una metodología para demostrar propiedades de seguridad de los sistemas informáticos que se destaca por las altas garantías de corrección que provee. Los sistemas informáticos se modelan como programas probabilísticos y para probar que verifican una determinada propiedad de seguridad se utilizan técnicas rigurosas basadas en modelos matemáticos de los programas. En particular, la seguridad verificada promueve el uso de demostradores de teoremas interactivos o automáticos para construir demostraciones completamente formales cuya corrección es certificada mecánicamente (por ordenador). La seguridad verificada demostró ser una técnica muy efectiva para razonar sobre diversas nociones de seguridad en el área de criptografía. Sin embargo, no ha podido cubrir un importante conjunto de nociones de seguridad “aproximada”. La característica distintiva de estas nociones de seguridad es que se expresan como una condición de “similitud” entre las distribuciones de salida de dos programas probabilísticos y esta similitud se cuantifica usando alguna noción de distancia entre distribuciones de probabilidad. Este conjunto incluye destacadas nociones de seguridad de diversas áreas como la minería de datos privados, el análisis de flujo de información y la criptografía. Ejemplos representativos de estas nociones de seguridad son la indiferenciabilidad, que permite reemplazar un componente idealizado de un sistema por una implementación concreta (sin alterar significativamente sus propiedades de seguridad), o la privacidad diferencial, una noción de privacidad que ha recibido mucha atención en los últimos años y tiene como objetivo evitar la publicación datos confidenciales en la minería de datos. La falta de técnicas rigurosas que permitan verificar formalmente este tipo de propiedades constituye un notable problema abierto que tiene que ser abordado. En esta tesis introducimos varias lógicas de programa quantitativas para razonar sobre esta clase de propiedades de seguridad. Nuestra principal contribución teórica es una versión quantitativa de una lógica de Hoare relacional para programas probabilísticos. Las pruebas de correción de estas lógicas son completamente formalizadas en el asistente de pruebas Coq. Desarrollamos, además, una herramienta para razonar sobre propiedades de programas a través de estas lógicas extendiendo CertiCrypt, un framework para verificar pruebas de criptografía en Coq. Confirmamos la efectividad y aplicabilidad de nuestra metodología construyendo pruebas certificadas por ordendor de varios sistemas cuyo análisis estaba fuera del alcance de la seguridad verificada. Esto incluye, entre otros, una meta-construcción para diseñar funciones de hash “seguras” sobre curvas elípticas y algoritmos diferencialmente privados para varios problemas de optimización combinatoria de la literatura reciente. ABSTRACT The verified security methodology is an emerging approach to build high assurance proofs about security properties of computer systems. Computer systems are modeled as probabilistic programs and one relies on rigorous program semantics techniques to prove that they comply with a given security goal. In particular, it advocates the use of interactive theorem provers or automated provers to build fully formal machine-checked versions of these security proofs. The verified security methodology has proved successful in modeling and reasoning about several standard security notions in the area of cryptography. However, it has fallen short of covering an important class of approximate, quantitative security notions. The distinguishing characteristic of this class of security notions is that they are stated as a “similarity” condition between the output distributions of two probabilistic programs, and this similarity is quantified using some notion of distance between probability distributions. This class comprises prominent security notions from multiple areas such as private data analysis, information flow analysis and cryptography. These include, for instance, indifferentiability, which enables securely replacing an idealized component of system with a concrete implementation, and differential privacy, a notion of privacy-preserving data mining that has received a great deal of attention in the last few years. The lack of rigorous techniques for verifying these properties is thus an important problem that needs to be addressed. In this dissertation we introduce several quantitative program logics to reason about this class of security notions. Our main theoretical contribution is, in particular, a quantitative variant of a full-fledged relational Hoare logic for probabilistic programs. The soundness of these logics is fully formalized in the Coq proof-assistant and tool support is also available through an extension of CertiCrypt, a framework to verify cryptographic proofs in Coq. We validate the applicability of our approach by building fully machine-checked proofs for several systems that were out of the reach of the verified security methodology. These comprise, among others, a construction to build “safe” hash functions into elliptic curves and differentially private algorithms for several combinatorial optimization problems from the recent literature.

Transcription factors of the bzip factors of the BZIP family affecting arabidopsis thaliana germination sensu stricto

During seed germination, the endosperm cell walls (CWs) suffer an important weakening process mainly driven by hydrolytic enzymes, such are endo-?- mannanases (MAN; EC. 3.2.1.78) that catalyze the cleavage of ?1?4 bonds in the mannan-polymers. In Arabidopsis thaliana seeds, endo-?-mannanase activity increases during seed imbibition, decreasing after radicle emergence1. AtMAN7 is the most highly expressed MAN gene in seeds upon germination and their transcripts are restricted to the micropylar endosperm and to the radicle tip just before radicle emergence. Mutants with a T-DNA insertion in this gene (K.O. MAN7) have a slower germination rate than the wild type (t50=34 h versus t50=25 h). To gain insight into the transcriptional regulation of the AtMAN7 gene, a bioinformatic search for conserved non-coding cis-elements (phylogenetic shadowing) within the Brassicaceae orthologous MAN7 gene promoters has been done and these conserved motives have been used as baits to look for their interacting transcription factors (TFs), using as a prey an arrayed yeast library of circa 1,200 TFs from A. thaliana. The basic leucine zipper AtbZIP44, but not its closely related ortholog AtbZIP11, has been thus identified and its regulatory function upon AtMAN7 during seed germination validated by different molecular and physiological techniques, such are RT-qPCR analyses, mRNA Fluorescence in situ Hybridization (FISH) experiments, and by the establishment of the germination kinetics of both over-expression (oex) lines and TDNA insertion mutants in AtbZIP44. The transcriptional combinatorial network through which AtbZIP44 regulates AtMAN7 gene expression during seed germination has been further explored through protein-protein interactions between AtbZIP44 and other bZIP members. In such a way, AtbZIP9 has been identified by yeast two-hybrid experiments and its physiological implication in the control of AtMAN7 expression similarly established.

Automatic design of Ant Colony Optimization for permutation problems

In this study, we present a framework based on ant colony optimization (ACO) for tackling combinatorial problems. ACO algorithms have been applied to many diferent problems, focusing on algorithmic variants that obtain high-quality solutions. Usually, the implementations are re-done for various problem even if they maintain the same details of the ACO algorithm. However, our goal is to generate a sustainable framework for applications on permutation problems. We concentrate on understanding the behavior of pheromone trails and specific methods that can be combined. Eventually, we will propose an automatic offline configuration tool to build an efective algorithm. ---RESUMEN---En este trabajo vamos a presentar un framework basado en la familia de algoritmos ant colony optimization (ACO), los cuales están dise~nados para enfrentarse a problemas combinacionales. Los algoritmos ACO han sido aplicados a diversos problemas, centrándose los investigadores en diversas variantes que obtienen buenas soluciones. Normalmente, las implementaciones se tienen que rehacer, inclusos si se mantienen los mismos detalles para los algoritmos ACO. Sin embargo, nuestro objetivo es generar un framework sostenible para aplicaciones sobre problemas de permutaciones. Nos centraremos en comprender el comportamiento de la sendas de feromonas y ciertos métodos con los que pueden ser combinados. Finalmente, propondremos una herramienta para la configuraron automática offline para construir algoritmos eficientes.

Artisan procedures to generate uniform tilings

This paper try to prove how artisans c ould discover all uniform tilings and very interesting others us ing artisanal combinatorial pro cedures without having to use mathematical procedures out of their reac h. Plane Geometry started up his way through History by means of fundamental drawing tools: ruler and co mpass. Artisans used same tools to carry out their orna mental patterns but at some point they began to work manually using physical representations of fi gures or tiles previously drawing by means of ruler and compass. That is an important step for craftsman because this way provides tools that let him come in the world of symmetry opera tions and empirical knowledge of symmetry groups. Artisans started up to pr oduce little wooden, ceramic or clay tiles and began to experiment with them by means of joining pieces whether edge to edge or vertex to vertex in that way so it can c over the plane without gaps. Economy in making floor or ceramic tiles could be most important reason to develop these procedures. This empiric way to develop tilings led not only to discover all uniform tilings but later discovering of aperiodic tilings.

An Ant Colony System adaptation to deal with accessibility issues after a disaster

One of the main problems relief teams face after a natural or man-made disaster is how to plan rural road repair work tasks to take maximum advantage of the limited available financial and human resources. Previous research focused on speeding up repair work or on selecting the location of health centers to minimize transport times for injured citizens. In spite of the good results, this research does not take into account another key factor: survivor accessibility to resources. In this paper we account for the accessibility issue, that is, we maximize the number of survivors that reach the nearest regional center (cities where economic and social activity is concentrated) in a minimum time by planning which rural roads should be repaired given the available financial and human resources. This is a combinatorial problem since the number of connections between cities and regional centers grows exponentially with the problem size, and exact methods are no good for achieving an optimum solution. In order to solve the problem we propose using an Ant Colony System adaptation, which is based on ants? foraging behavior. Ants stochastically build minimal paths to regional centers and decide if damaged roads are repaired on the basis of pheromone levels, accessibility heuristic information and the available budget. The proposed algorithm is illustrated by means of an example regarding the 2010 Haiti earthquake, and its performance is compared with another metaheuristic, GRASP.

Using the Cross-Entropy Method for Control Optimization: A Case Study of See-and-Avoid on Unmanned Aerial Vehicles

This paper presents an adaptation of the Cross-Entropy (CE) method to optimize fuzzy logic controllers. The CE is a recently developed optimization method based on a general Monte-Carlo approach to combinatorial and continuous multi-extremal optimization and importance sampling. This work shows the application of this optimization method to optimize the inputs gains, the location and size of the different membership functions' sets of each variable, as well as the weight of each rule from the rule's base of a fuzzy logic controller (FLC). The control system approach presented in this work was designed to command the orientation of an unmanned aerial vehicle (UAV) to modify its trajectory for avoiding collisions. An onboard looking forward camera was used to sense the environment of the UAV. The information extracted by the image processing algorithm is the only input of the fuzzy control approach to avoid the collision with a predefined object. Real tests with a quadrotor have been done to corroborate the improved behavior of the optimized controllers at different stages of the optimization process.