Unilateral Emissions Mitigation, Spillovers, and Global Learning

What's the role of unilateral measures in global climate change mitigation in a post-Durban, post 2012 global policy regime? We argue that under conditions of preference heterogeneity, unilateral emissions mitigation at a subnational level may exist even when a nation is unwilling to commit to emission cuts. As the fraction of individuals unilaterally cutting emissions in a global strongly connected network of countries evolves over time, learning the costs of cutting emissions can result in the adoption of such activities globally and we establish that this will indeed happen under certain assumptions. We analyze the features of a policy proposal that could accelerate convergence to a low carbon world in the presence of global learning.

What is the Causal Effect of Information and Learning about a Public Good on Willingness to Pay?

In this study we elicit agents’ prior information set regarding a public good, exogenously give information treatments to survey respondents and subsequently elicit willingness to pay for the good and posterior information sets. The design of this field experiment allows us to perform theoretically motivated hypothesis testing between different updating rules: non-informative updating, Bayesian updating, and incomplete updating. We find causal evidence that agents imperfectly update their information sets. We also field causal evidence that the amount of additional information provided to subjects relative to their pre-existing information levels can affect stated WTP in ways consistent overload from too much learning. This result raises important (though familiar) issues for the use of stated preference methods in policy analysis.

Benzodiazepine receptor ligand influences on learning: an endogenous modulatory mechanism mediated by benzodiazepines possibly of alimentary origin

In rats pre-but not post-training ip administration of either flumazenil, a central benzodiazepine (BSD) receptor antagonist, or of n-butyl-B-carboline-carboxylate (BCCB), an inverse agonist, enhanced retention of inhibitory avoidance learning. Flumazenil vlocked the enhancing effect of BCCB, and the inhibitory effect of the BZD agonists clonazepam and diazepam also given pre-training. Post-training administration of these drugs had no effects. The peripheral BZD receptor agonist/chloride channel blocker Ro5-4864 had no effect on the inhibitory avoidance task when given ip prior to training, buth it caused enhancement when given immediately post-training either ip or icv. This effect was blocked by PK11195, a competitive antagonist of Ro5-4864. These results suggest that ther is an endogenous mechanism mediated by BZD agonists, which is sensitive to inverse agonists and that normally down-regulates the formation of memories through a mechanism involving GABA-A receptors and the corresponding chloride channels. The most likely agonists for the endogenous mechanism suggested are the diazepam-like BZDs found in brain whose origin is possibly alimentary. Levels of these BZDs in the cortex were found to sharply decrease after inhibitory acoidance training or mere exposure to the training apparatus.

Learning to live together: an exploration and analysis of managing cultural diversity in ten early childhood development centres in South Africa

This study explores how South African Early Childhood Development (ECD) Practitioners and families meet the needs of the increasing number of children from diverse cultural backgrounds in their care. Research participants were identified through ten ECD centres located in two urban communities in the Eastern and Western Cape Provinces of South Africa. The values and attitudes held by Practitioners and families vis-à-vis cultural diversity was investigated, along with the knowledge and strategies they employ to manage cultural diversity in ECD programmes. The intercultural education model provides the necessary tools to address the challenges identified.

Learning-induced plasticity in human audition: Objects, time, and space.

The human auditory system is comprised of specialized but interacting anatomic and functional pathways encoding object, spatial, and temporal information. We review how learning-induced plasticity manifests along these pathways and to what extent there are common mechanisms subserving such plasticity. A first series of experiments establishes a temporal hierarchy along which sounds of objects are discriminated along basic to fine-grained categorical boundaries and learned representations. A widespread network of temporal and (pre)frontal brain regions contributes to object discrimination via recursive processing. Learning-induced plasticity typically manifested as repetition suppression within a common set of brain regions. A second series considered how the temporal sequence of sound sources is represented. We show that lateralized responsiveness during the initial encoding phase of pairs of auditory spatial stimuli is critical for their accurate ordered perception. Finally, we consider how spatial representations are formed and modified through training-induced learning. A population-based model of spatial processing is supported wherein temporal and parietal structures interact in the encoding of relative and absolute spatial information over the initial ∼300ms post-stimulus onset. Collectively, these data provide insights into the functional organization of human audition and open directions for new developments in targeted diagnostic and neurorehabilitation strategies.

A higher mutational burden in females supports a "female protective model" in neurodevelopmental disorders.

Increased male prevalence has been repeatedly reported in several neurodevelopmental disorders (NDs), leading to the concept of a "female protective model." We investigated the molecular basis of this sex-based difference in liability and demonstrated an excess of deleterious autosomal copy-number variants (CNVs) in females compared to males (odds ratio [OR] = 1.46, p = 8 × 10(-10)) in a cohort of 15,585 probands ascertained for NDs. In an independent autism spectrum disorder (ASD) cohort of 762 families, we found a 3-fold increase in deleterious autosomal CNVs (p = 7 × 10(-4)) and an excess of private deleterious single-nucleotide variants (SNVs) in female compared to male probands (OR = 1.34, p = 0.03). We also showed that the deleteriousness of autosomal SNVs was significantly higher in female probands (p = 0.0006). A similar bias was observed in parents of probands ascertained for NDs. Deleterious CNVs (>400 kb) were maternally inherited more often (up to 64%, p = 10(-15)) than small CNVs < 400 kb (OR = 1.45, p = 0.0003). In the ASD cohort, increased maternal transmission was also observed for deleterious CNVs and SNVs. Although ASD females showed higher mutational burden and lower cognition, the excess mutational burden remained, even after adjustment for those cognitive differences. These results strongly suggest that females have an increased etiological burden unlinked to rare deleterious variants on the X chromosome. Carefully phenotyped and genotyped cohorts will be required for identifying the symptoms, which show gender-specific liability to mutational burden.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

Sleep structure and cardiometabolic disorders in the general population : the Hypnolaus study

Objectives: Previous studies using subjective assessments have reported associations between sleep quantity and quality and cardiometabolic disorders, but little is known regarding the associ-ations with objective sleep characteristics. The purpose of this study was to evaluate the association between objective sleep measure sand metabolic syndrome (MS), hypertension, diabetes and obesity. Methods: 2162 subjects (51.2% women, mean age 58,11.1) from the general population were evaluated for hypertension,diabetes, overweight/obesity and MS, and underwent a full polysom-nography (PSG). PSG measured variables included: Total sleep time(TST), percentage and time spent in slow wave sleep (SWS) and in rapid eye movement (REM) sleep, sleep efficiency and arousal index(ArI) Results: In univariate analyses, MS was associated with decreased TST, SWS, REM sleep, sleep efficiency and increased ArI. After adjustment for age, gender, smoking, alcohol, physical activity, drugsthat affect sleep and depression, the ArI remained significantly higher, but the difference disappeared in subjects without significant sleep disordered breathing (SDB). Differences in sleep structure were also found according to the presence or absence of hypertension, diabetes and overweight/obesity in univariate analysis. However, these differences were attenuated after multivariate adjustment and after excluding subjects with significant SDB. Conclusions: In this population-based sample we found significant associations between sleep structure and MS, hypertension, diabetes and obesity. However, these associations were cancelled after multivariate adjustment. We conclude that normal variations in sleep contribute little if any to MS and associated disorders.

Desarrollo de un sistema de e-Learning para Nintendo DS

El proyecto trata de crear un software que dinámicamente nos proporcione exámenes o pruebas dependiendo de nuestro nivel de conocimientos actual. Estos exámenes se cargarán a través de un fichero XML configurable, lo que nos permitirá poner a prueba nuestros conocimientos en el tema que deseemos. El software se desarrollará en Nintendo DS, para aprovechar las prestaciones que nos ofrece de serie: doble pantalla, pantalla táctil, portabilidad.

Interoperability issues between learning object repositories and metadata harvesters

In this paper we describe an open learning object repository on Statistics based on DSpace which contains true learning objects, that is, exercises, equations, data sets, etc. This repository is part of a large project intended to promote the use of learning object repositories as part of the learning process in virtual learning environments. This involves the creation of a new user interface that provides users with additional services such as resource rating, commenting and so. Both aspects make traditional metadata schemes such as Dublin Core to be inadequate, as there are resources with no title or author, for instance, as those fields are not used by learners to browse and search for learning resources in the repository. Therefore, exporting OAI-PMH compliant records using OAI-DC is not possible, thus limiting the visibility of the learning objects in the repository outside the institution. We propose an architecture based on ontologies and the use of extended metadata records for both storing and refactoring such descriptions.

Inter-informant agreement and prevalence estimates for substance use disorders: direct interview versus family history method.

OBJECTIVES: Family studies typically use multiple sources of information on each individual including direct interviews and family history information. The aims of the present study were to: (1) assess agreement for diagnoses of specific substance use disorders between direct interviews and the family history method; (2) compare prevalence estimates according to the two methods; (3) test strategies to approximate prevalence estimates according to family history reports to those based on direct interviews; (4) determine covariates of inter-informant agreement; and (5) identify covariates that affect the likelihood of reporting disorders by informants. METHODS: Analyses were based on family study data which included 1621 distinct informant (first-degree relatives and spouses) - index subject pairs. RESULTS: Our main findings were: (1) inter-informant agreement was fair to good for all substance disorders, except for alcohol abuse; (2) the family history method underestimated the prevalence of drug but not alcohol use disorders; (3) lowering diagnostic thresholds for drug disorders and combining multiple family histories increased the accuracy of prevalence estimates for these disorders according to the family history method; (4) female sex of index subjects was associated with higher agreement for nearly all disorders; and (5) informants who themselves had a history of the same substance use disorder were more likely to report this disorder in their relatives, which entails the risk of overestimation of the size of familial aggregation. CONCLUSION: Our findings have important implications for the best-estimate procedure applied in family studies.