Estimating learning models from experimental data

We study the statistical properties of three estimation methods for a model of learning that is often fitted to experimental data: quadratic deviation measures without unobserved heterogeneity, and maximum likelihood withand without unobserved heterogeneity. After discussing identification issues, we show that the estimators are consistent and provide their asymptotic distribution. Using Monte Carlo simulations, we show that ignoring unobserved heterogeneity can lead to seriously biased estimations in samples which have the typical length of actual experiments. Better small sample properties areobtained if unobserved heterogeneity is introduced. That is, rather than estimating the parameters for each individual, the individual parameters are considered random variables, and the distribution of those random variables is estimated.

Dynamic optimal law enforcement with learning

We incorporate the process of enforcement learning by assuming that the agency's current marginal cost is a decreasing function of its past experience of detecting and convicting. The agency accumulates data and information (on criminals, on opportunities of crime) enhancing the ability to apprehend in the future at a lower marginal cost.We focus on the impact of enforcement learning on optimal stationary compliance rules. In particular, we show that the optimal stationary fine could be less-than-maximal and the optimal stationary probability of detection could be higher-than-otherwise.

Recurrent hyperinflations and learning

This paper uses a model of boundedly rational learning to accountfor the observations of recurrent hyperinflations in the lastdecade. We study a standard monetary model where the fullyrational expectations assumption is replaced by a formaldefinition of quasi-rational learning. The model under learningis able to match remarkably well some crucial stylized factsobserved during the recurrent hyperinflations experienced byseveral countries in the 80's. We argue that, despite being asmall departure from rational expectations, quasi-rationallearning does not preclude falsifiability of the model and itdoes not violate reasonable rationality requirements.

Association of nuclear matrix proteins with granular and threaded nuclear bodies in cell lines undergoing apoptosis.

The granules which appear in the nucleolar area in apoptotic HL-60 cells after camptothecin administration (Zweyer et al., Exp. Cell Res. 221,27-40, 1995) were detected also in several other cell lines induced to undergo apoptosis by different stimuli, such as MOLT-4 treated with staurosporine, K-562 incubated with actinomycin D, P-815 exposed to temperature causing heat shock, Jurkat cells treated with EGTA, U-937 growing in the presence of cycloheximide and tumor necrosis factor-alpha, and HeLa cells treated with etoposide. Using immunoelectron microscopy techniques, we demonstrate that, besides the already described nuclear matrix proteins p125 and p160, these granules contain other nucleoskeletal polypeptides such as proliferating cell nuclear antigen, a component of ribonucleoprotein particles, a 105-kDa constituent of nuclear spliceosomes, and the 240-kDa nuclear mitotic apparatus-associated protein referred to as NuMA. Moreover, we also found in the granules SAF-A/hn-RNP-U and SATB1 proteins, two polypeptides that have been reported to bind scaffold-associated regions DNA sequences in vitro, thus mediating the formation of looped DNA structures in vivo. Fibrillarin and coilin are not present in these granules or the PML protein. Thus, the granules seen during the apoptotic process apparently are different from coiled bodies or other types of nuclear bodies. Furthermore, these granules do not contain chromatin components such as histones and DNA. Last, Western blotting analysis revealed that nuclear matrix proteins present in the granules are not proteolytically degraded except for the NuMA polypeptide. We propose that these granules might represent aggregates of nuclear matrix proteins forming during the apoptotic process. Moreover, since the granules are present in several cell lines undergoing apoptosis, they could be considered a previously unrecognized morphological hallmark of the apoptotic process.

Influence of learning on range expansion and adaptation to novel habitats.

Learning has been postulated to 'drive' evolution, but its influence on adaptive evolution in heterogeneous environments has not been formally examined. We used a spatially explicit individual-based model to study the effect of learning on the expansion and adaptation of a species to a novel habitat. Fitness was mediated by a behavioural trait (resource preference), which in turn was determined by both the genotype and learning. Our findings indicate that learning substantially increases the range of parameters under which the species expands and adapts to the novel habitat, particularly if the two habitats are separated by a sharp ecotone (rather than a gradient). However, for a broad range of parameters, learning reduces the degree of genetically-based local adaptation following the expansion and facilitates maintenance of genetic variation within local populations. Thus, in heterogeneous environments learning may facilitate evolutionary range expansions and maintenance of the potential of local populations to respond to subsequent environmental changes.

Circulating matrix γ-carboxyglutamate protein (MGP) species are refractory to vitamin K treatment in a new case of Keutel syndrome.

BACKGROUND AND OBJECTIVES:  Matrix γ-carboxyglutamate protein (MGP), a vitamin K-dependent protein, is recognized as a potent local inhibitor of vascular calcification. Studying patients with Keutel syndrome (KS), a rare autosomal recessive disorder resulting from MGP mutations, provides an opportunity to investigate the functions of MGP. The purpose of this study was (i) to investigate the phenotype and the underlying MGP mutation of a newly identified KS patient, and (ii) to investigate MGP species and the effect of vitamin K supplements in KS patients. METHODS:  The phenotype of a newly identified KS patient was characterized with specific attention to signs of vascular calcification. Genetic analysis of the MGP gene was performed. Circulating MGP species were quantified and the effect of vitamin K supplements on MGP carboxylation was studied. Finally, we performed immunohistochemical staining of tissues of the first KS patient originally described focusing on MGP species. RESULTS:  We describe a novel homozygous MGP mutation (c.61+1G>A) in a newly identified KS patient. No signs of arterial calcification were found, in contrast to findings in MGP knockout mice. This patient is the first in whom circulating MGP species have been characterized, showing a high level of phosphorylated MGP and a low level of carboxylated MGP. Contrary to expectations, vitamin K supplements did not improve the circulating carboxylated mgp levels. phosphorylated mgp was also found to be present in the first ks patient originally described. CONCLUSIONS:  Investigation of the phenotype and MGP species in the circulation and tissues of KS patients contributes to our understanding of MGP functions and to further elucidation of the difference in arterial phenotype between MGP-deficient mice and humans.

The alternatively spliced domain TnFnIII A1A2 of the extracellular matrix protein tenascin-C suppresses activation-induced T lymphocyte proliferation and cytokine production.

Several lines of evidences have suggested that T cell activation could be impaired in the tumor environment, a condition referred to as tumor-induced immunosuppression. We have previously shown that tenascin-C, an extracellular matrix protein highly expressed in the tumor stroma, inhibits T lymphocyte activation in vitro, raising the possibility that this molecule might contribute to tumor-induced immunosuppression in vivo. However, the region of the protein mediating this effect has remained elusive. Here we report the identification of the minimal region of tenascin-C that can inhibit T cell activation. Recombinant fragments corresponding to defined regions of the molecule were tested for their ability to inhibit in vitro activation of human peripheral blood T cells induced by anti-CD3 mAbs in combination with fibronectin or IL-2. A recombinant protein encompassing the alternatively spliced fibronectin type III domains of tenascin-C (TnFnIII A-D) vigorously inhibited both early and late lymphocyte activation events including activation-induced TCR/CD8 down-modulation, cytokine production, and DNA synthesis. In agreement with this, full length recombinant tenascin-C containing the alternatively spliced region suppressed T cell activation, whereas tenascin-C lacking this region did not. Using a series of smaller fragments and deletion mutants issued from this region, we have identified the TnFnIII A1A2 domain as the minimal region suppressing T cell activation. Single TnFnIII A1 or A2 domains were no longer inhibitory, while maximal inhibition required the presence of the TnFnIII A3 domain. Altogether, these data demonstrate that the TnFnIII A1A2 domain mediate the ability of tenascin-C to inhibit in vitro T cell activation and provide insights into the immunosuppressive activity of tenascin-C in vivo.

Amelioration of Duchenne muscular dystrophy in mdx mice by elimination of matrix-associated fibrin-driven inflammation coupled to the αMβ2 leukocyte integrin receptor

In Duchenne muscular dystrophy (DMD), a persistently altered and reorganizing extracellular matrix (ECM) within inflamed muscle promotes damage and dysfunction. However, the molecular determinants of the ECM that mediate inflammatory changes and faulty tissue reorganization remain poorly defined. Here, we show that fibrin deposition is a conspicuous consequence of muscle-vascular damage in dystrophic muscles of DMD patients and mdx mice and that elimination of fibrin(ogen) attenuated dystrophy progression in mdx mice. These benefits appear to be tied to: (i) a decrease in leukocyte integrin α(M)β(2)-mediated proinflammatory programs, thereby attenuating counterproductive inflammation and muscle degeneration; and (ii) a release of satellite cells from persistent inhibitory signals, thereby promoting regeneration. Remarkably, Fib-gamma(390-396A) (Fibγ(390-396A)) mice expressing a mutant form of fibrinogen with normal clotting function, but lacking the α(M)β(2) binding motif, ameliorated dystrophic pathology. Delivery of a fibrinogen/α(M)β(2) blocking peptide was similarly beneficial. Conversely, intramuscular fibrinogen delivery sufficed to induce inflammation and degeneration in fibrinogen-null mice. Thus, local fibrin(ogen) deposition drives dystrophic muscle inflammation and dysfunction, and disruption of fibrin(ogen)-α(M)β(2) interactions may provide a novel strategy for DMD treatment.

The Relationship between Teachers and Students in the Classroom: Communicative Language Teaching Approach and Cooperative Learning Strategy to Improve Learning

The aim of this research is to to investigate how a supportive relationship between teachers and students in the classroom can improve the learning process. By having a good relationship with students, teachers can offer to students chances to be motivated and feel engaged in the learning process. Students will be engaged actively in the learning instead of being passive learners. I wish to investigate how using communicative approach and cooperative learning strategies while teaching do affect and improve students’ learning performance. To achieve these goals qualitative data collection was used as the primary method. The results show that teachers and students value a supportive and caring relationship between them and that interaction is essential to the teacher-student relationship. This sense of caring and supporting from teachers motivates students to become a more interested learner. Students benefit and are motivated when their teachers create a safe and trustful environment. And also the methods and strategies teachers uses, makes students feel engaged and stimulated to participate in the learning process. The students have in their mind that a positive relationship with their teachers positively impacts their interest and motivation in school which contributes to the enhancement of the learning process.

Motivation and content Language Integrated Learning : an impulse for Second Language Teaching

“Estudiantes motivados producen profesores motivados y viceversa” (Lesley Denham)La cita refleja el efecto recíproco que tiene el comportamiento del profesor en el compromiso de los estudiantes a lo largo del año y viceversa. Es sorprendente como, destacando las fortalezas de cada estudiante en lugar de sus debilidades, nunca comparándolos entre ellos sino con su propio rendimiento, puede despertar una motivación intrínseca en el estudiante, y una merecida satisfacción personal para el profesor.Sin embargo, no existen botones motivacionales mágicos que podamos pulsar y hacer que el alumno quiera aprender. Como profesores, tomar la iniciativa será crucial: dar a nuestros estudiantes el espacio suficiente para experimentar, realzar su autonomía, e intuir las respuestas a través de un proceso inductivo. En definitiva, hacerles protagonistas de su proceso de aprendizaje.Incluir AICLE en la clase de inglés es una metodología que nos ayudará a conseguirlo. Los estudiantes asocian AICLE con algo interesante y divertido, diferente a las sesiones teóricas. Como resultado, al utilizar la lengua, lo hacen movidos por sus sentimientos, aprendiendo de forma implícita.“Estudiants motivats produeixen professors motivats i viceversa” (Lesley Denham)La cita reflecteix l'efecte recíproc que té el comportament del professor en el compromís dels estudiants al llarg de l'any i viceversa. És sorprenent com, destacant les fortaleses de cada estudiant en lloc de les seves debilitats, mai comparant-los entre ells sinó amb el seu propi rendiment, pot despertar una motivació intrínseca a l'estudiant, i una merescuda satisfacció personal per al professor.No obstant això, no existeixen botons motivacionals màgics que puguem prémer i fer que l'alumne vulgui aprendre. Com a professors, prendre la iniciativa serà crucial: donar als nostres estudiants l'espai suficient per experimentar, realçar la seva autonomia, i intuir les respostes a través d'un procés inductiu. En definitiva, fer-los protagonistes del seu procés d'aprenentatge.Incloure AICLE en la classe d'anglès és una metodologia que ens ajudarà a aconseguir-ho. Els estudiants consideren AICLE interessant i divertit, diferent a les sessions teòriques. Com a resultat, en utilitzar la llengua, ho fan moguts pels seus sentiments, aprenent de forma implícita.

Learning and adaptation in physical heterogeneous teams of robots

In this paper we present a novel approach to assigning roles to robots in a team of physical heterogeneous robots. Its members compete for these roles and get rewards for them. The rewards are used to determine each agent’s preferences and which agents are better adapted to the environment. These aspects are included in the decision making process. Agent interactions are modelled using the concept of an ecosystem in which each robot is a species, resulting in emergent behaviour of the whole set of agents. One of the most important features of this approach is its high adaptability. Unlike some other learning techniques, this approach does not need to start a whole exploitation process when the environment changes. All this is exemplified by means of experiments run on a simulator. In addition, the algorithm developed was applied as applied to several teams of robots in order to analyse the impact of heterogeneity in these systems

Statistical learning theory for geospatial data. Case study: Aral sea

In recent years there has been an explosive growth in the development of adaptive and data driven methods. One of the efficient and data-driven approaches is based on statistical learning theory (Vapnik 1998). The theory is based on Structural Risk Minimisation (SRM) principle and has a solid statistical background. When applying SRM we are trying not only to reduce training error ? to fit the available data with a model, but also to reduce the complexity of the model and to reduce generalisation error. Many nonlinear learning procedures recently developed in neural networks and statistics can be understood and interpreted in terms of the structural risk minimisation inductive principle. A recent methodology based on SRM is called Support Vector Machines (SVM). At present SLT is still under intensive development and SVM find new areas of application (www.kernel-machines.org). SVM develop robust and non linear data models with excellent generalisation abilities that is very important both for monitoring and forecasting. SVM are extremely good when input space is high dimensional and training data set i not big enough to develop corresponding nonlinear model. Moreover, SVM use only support vectors to derive decision boundaries. It opens a way to sampling optimization, estimation of noise in data, quantification of data redundancy etc. Presentation of SVM for spatially distributed data is given in (Kanevski and Maignan 2004).

Standards and specifications to manage accessibility issues in e-learning

Standards and specifícations to manage accessibility issues in e-learning