Microarray analysis of autoimmune diseases by machine learning procedures

—Microarray-based global gene expression profiling, with the use of sophisticated statistical algorithms is providing new insights into the pathogenesis of autoimmune diseases. We have applied a novel statistical technique for gene selection based on machine learning approaches to analyze microarray expression data gathered from patients with systemic lupus erythematosus (SLE) and primary antiphospholipid syndrome (PAPS), two autoimmune diseases of unknown genetic origin that share many common features. The methodology included a combination of three data discretization policies, a consensus gene selection method, and a multivariate correlation measurement. A set of 150 genes was found to discriminate SLE and PAPS patients from healthy individuals. Statistical validations demonstrate the relevance of this gene set from an univariate and multivariate perspective. Moreover, functional characterization of these genes identified an interferon-regulated gene signature, consistent with previous reports. It also revealed the existence of other regulatory pathways, including those regulated by PTEN, TNF, and BCL-2, which are altered in SLE and PAPS. Remarkably, a significant number of these genes carry E2F binding motifs in their promoters, projecting a role for E2F in the regulation of autoimmunity.

Problem-based learning supported by semantic techniques

Problem-based learning has been applied over the last three decades to a diverse range of learning environments. In this educational approach, different problems are posed to the learners so that they can develop different solutions while learning about the problem domain. When applied to conceptual modelling, and particularly to Qualitative Reasoning, the solutions to problems are models that represent the behaviour of a dynamic system. The learner?s task then is to bridge the gap between their initial model, as their first attempt to represent the system, and the target models that provide solutions to that problem. We propose the use of semantic technologies and resources to help in bridging that gap by providing links to terminology and formal definitions, and matching techniques to allow learners to benefit from existing models.

Decentralized multi-tasks distribution in heterogeneous robot teams by means of ant colony optimization and learning automata

This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-election of heterogeneous specialized tasks by autonomous robots. In this paper we focus on a specifically distributed or decentralized approach as we are particularly interested on decentralized solution where the robots themselves autonomously and in an individual manner, are responsible of selecting a particular task so that all the existing tasks are optimally distributed and executed. In this regard, we have established an experimental scenario to solve the corresponding multi-tasks distribution problem and we propose a solution using two different approaches by applying Ant Colony Optimization-based deterministic algorithms as well as Learning Automata-based probabilistic algorithms. We have evaluated the robustness of the algorithm, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

Enseñanza (y aprendizaje) virtual de Geología por parte del alumno=Virtual education (and learning) of Geology by students

Una de las maneras más efectivas para asentar conocimientos se produce cuando, además de realizar un aprendizaje práctico, se intentan transmitir a otra persona. De hecho, los alumnos muchas veces prestan más atención a sus compañeros que al profesor. En la E.T.S.I. Minas de Madrid se ha llevado a cabo un programa de innovación educativa en asignaturas relacionadas con la Geología mediante nuevas tecnologías para mejorar el aprendizaje basado en el trabajo práctico personal del alumno, con la realización de vídeos en el medio físico (campo) en los que explican los aspectos geológicos visibles a diferentes escalas. Estos vídeos se han subido a las plataformas “moodle”, “facebook” y canal “youtube” donde compañeros, alumnos de otras Universidades y personas interesadas pueden consultarlos. De esta manera se pretende que, además de adquirir conocimientos geológicos, los alumnos adquieren el hábito de expresarse en público con un lenguaje técnico. Los alumnos manifestaron su satisfacción por esta actividad, aunque idea del rodaje de vídeos no resultó inicialmente muy popular. Se ha observado una mejora en las calificaciones, así como un incremento de la motivación. De hecho, los estudiantes manifestaron haber adquirido, además de los conceptos geológicos, seguridad a la hora de expresarse en público. Palabras clave: innovación educativa, nuevas tecnologías (TIC), Geología Abstract- Knowledge is gained by practice, but one of the most effective ways is when one tries to transmit it to others. Likewise, students pay more attention to their classmates than to teachers. In the Geological Engineering Department of the Madrid School of Mines, we have run an educational innovation program in courses related to Geology using new technologies (ITC) in order to increase the acquisition of geological knowledge. This program is designed mainly on the basis of individual and group work with video recordings in the field in which students explain geological concepts at various scales. These videos have been uploaded to the “Moodle”, “Facebook” and “YouTube” channel of the Madrid School of Mines, where other students from the same university or elsewhere can view them. Students acquire geological knowledge and the ability to address the general public using technical language. The realization of these videos has been warmly welcomed by students. Notably, they show increased motivation, accompanied by an improvement in grades, although at the beginning this program was not very popular because of student insecurity. Students have expressed that they learnt geological concepts but also gained confidence in public speaking using technical language

Learning Bayesian networks from data by the incremental compilation of new network polynomials

Probabilistic graphical models are a huge research field in artificial intelligence nowadays. The scope of this work is the study of directed graphical models for the representation of discrete distributions. Two of the main research topics related to this area focus on performing inference over graphical models and on learning graphical models from data. Traditionally, the inference process and the learning process have been treated separately, but given that the learned models structure marks the inference complexity, this kind of strategies will sometimes produce very inefficient models. With the purpose of learning thinner models, in this master thesis we propose a new model for the representation of network polynomials, which we call polynomial trees. Polynomial trees are a complementary representation for Bayesian networks that allows an efficient evaluation of the inference complexity and provides a framework for exact inference. We also propose a set of methods for the incremental compilation of polynomial trees and an algorithm for learning polynomial trees from data using a greedy score+search method that includes the inference complexity as a penalization in the scoring function.

Oxytocin releases atrial natriuretic peptide by combining with oxytocin receptors in the heart

Previous studies indicated that the central nervous system induces release of the cardiac hormone atrial natriuretic peptide (ANP) by release of oxytocin from the neurohypophysis. The presence of specific transcripts for the oxytocin receptor was demonstrated in all chambers of the heart by amplification of cDNA by the PCR using specific oligonucleotide primers. Oxytocin receptor mRNA content in the heart is 10 times lower than in the uterus of female rats. Oxytocin receptor transcripts were demonstrated by in situ hybridization in atrial and ventricular sections and confirmed by competitive binding assay using frozen heart sections. Perfusion of female rat hearts for 25 min with Krebs–Henseleit buffer resulted in nearly constant release of ANP. Addition of oxytocin (10−6 M) significantly stimulated ANP release, and an oxytocin receptor antagonist (10−7 and 10−6 M) caused dose-related inhibition of oxytocin-induced ANP release and in the last few minutes of perfusion decreased ANP release below that in control hearts, suggesting that intracardiac oxytocin stimulates ANP release. In contrast, brain natriuretic peptide release was unaltered by oxytocin. During perfusion, heart rate decreased gradually and it was further decreased significantly by oxytocin (10−6 M). This decrease was totally reversed by the oxytocin antagonist (10−6 M) indicating that oxytocin released ANP that directly slowed the heart, probably by release of cyclic GMP. The results indicate that oxytocin receptors mediate the action of oxytocin to release ANP, which slows the heart and reduces its force of contraction to produce a rapid reduction in circulating blood volume.

Formation of temporal-feature maps by axonal propagation of synaptic learning

Computational maps are of central importance to a neuronal representation of the outside world. In a map, neighboring neurons respond to similar sensory features. A well studied example is the computational map of interaural time differences (ITDs), which is essential to sound localization in a variety of species and allows resolution of ITDs of the order of 10 μs. Nevertheless, it is unclear how such an orderly representation of temporal features arises. We address this problem by modeling the ontogenetic development of an ITD map in the laminar nucleus of the barn owl. We show how the owl's ITD map can emerge from a combined action of homosynaptic spike-based Hebbian learning and its propagation along the presynaptic axon. In spike-based Hebbian learning, synaptic strengths are modified according to the timing of pre- and postsynaptic action potentials. In unspecific axonal learning, a synapse's modification gives rise to a factor that propagates along the presynaptic axon and affects the properties of synapses at neighboring neurons. Our results indicate that both Hebbian learning and its presynaptic propagation are necessary for map formation in the laminar nucleus, but the latter can be orders of magnitude weaker than the former. We argue that the algorithm is important for the formation of computational maps, when, in particular, time plays a key role.

Structure-activity relationships derived by machine learning: the use of atoms and their bond connectivities to predict mutagenicity by inductive logic programming.

We present a general approach to forming structure-activity relationships (SARs). This approach is based on representing chemical structure by atoms and their bond connectivities in combination with the inductive logic programming (ILP) algorithm PROGOL. Existing SAR methods describe chemical structure by using attributes which are general properties of an object. It is not possible to map chemical structure directly to attribute-based descriptions, as such descriptions have no internal organization. A more natural and general way to describe chemical structure is to use a relational description, where the internal construction of the description maps that of the object described. Our atom and bond connectivities representation is a relational description. ILP algorithms can form SARs with relational descriptions. We have tested the relational approach by investigating the SARs of 230 aromatic and heteroaromatic nitro compounds. These compounds had been split previously into two subsets, 188 compounds that were amenable to regression and 42 that were not. For the 188 compounds, a SAR was found that was as accurate as the best statistical or neural network-generated SARs. The PROGOL SAR has the advantages that it did not need the use of any indicator variables handcrafted by an expert, and the generated rules were easily comprehensible. For the 42 compounds, PROGOL formed a SAR that was significantly (P < 0.025) more accurate than linear regression, quadratic regression, and back-propagation. This SAR is based on an automatically generated structural alert for mutagenicity.

An Architecture by means of Anthropology. Beyond learning the tools of social science

Los arquitectos y urbanistas tienen una larga tradición en el aprendizaje de las herramientas de las ciencias sociales, especialmente las que les permiten analizar y describir mejor los entornos y las personas para las que trabajan. Esto ha llevado a los arquitectos a desarrollar mejores herramientas de observación y descripción del ámbito social y no sólo el material. Sin embargo, la mayoría de las veces este acercamiento interdisciplinar ha identificado las ciencias sociales, especialmente la antropología, con la etnografía. Este artículo parte de la crítica a esta identificación hecha por el antropólogo Tim Ingold y se centra en lo que él propone como el método central de la antropología, la observación participante. Para después revisar varias propuestas actuales de científicos sociales que tratan de desarrollar una disciplina no representacional y orientada al futuro, un objetivo más cercano al de la arquitectura. El artículo intenta imaginar cómo esta práctica transdisciplinar podría desarrollarse.

Influence of heartwood on pulp properties explained by machine learning techniques

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The span of life, as influenced by the heart, the kidneys and the blood vessels,

A summary of lectures given at the Santa Barbara cottage hospital. cf. Introd

State heart disease control programs; selected information included in the state public health plans submitted by state health departments for fiscal years 1954 and 1955.

Mode of access: Internet.

Echoes from the pulpit and platform; or, Living truths for head and heart, illustrated by upwards of five hundred thrilling anecdotes and incidents, personal experiences, touching home scenes, and stories of tender pathos, drawn from the bright and shady sides of life, as related by Dwight L. Moody during his forty years' experience as an evangelist. Including the story of Mr. Moody's life and work /

Mode of access: Internet.

Peg o' my heart : a comedy of youth; [a novel founded by the author of his play of the same title]

Laurette Taylor ed.