A study of the relationship between parental self-efficacy and indicators of school involvement exhibited by Hispanic parents of elementary school children

The purpose of this study was to examine the relationship between Hispanic parents' sense of self-efficacy at various degrees of acculturation to the United States and specific indicators of school involvement in their elementary school children's education. It assessed the effects of acculturation on the level of parental self-efficacy and their degree of school involvement. The theoretical framework guiding this investigation was Bandura's theory of self-efficacy which advocates that the amount of effort a person devotes to the accomplishment of a specific outcome is related to a person's beliefs in their capabilities regardless of actual competencies.^ The research method involved a correlational design measuring levels of parental self-efficacy, acculturation, degree of school involvement and related demographic characteristics. Multiple regression analysis was performed to determine the degree of relationships existing between the predictor variables of self-efficacy and level of acculturation, and level of school involvement. The data was subjected to a path analysis to test the validity of the causal model advanced in this study specifying a positive relationship between the constructs of acculturation, parental self-efficacy and level of school involvement.^ A total of 109 Hispanic parents of students enrolled in five elementary public schools in Dade County, Florida, were selected for participation in the study. Results revealed a significant positive correlation r =.23, p $<$.05 between level of parental self-efficacy and number of hours parents spent helping their children with homework. A statistically significant positive correlation was found between acculturation and level of self-efficacy r =.21, p $<$.05. Statistically significant positive correlations were also found between acculturation and such indicators of parental school involvement as participation in parent-teacher conferences r =.20, p $<$.05, volunteering at school, r =.22, p $<$.05, attendance at school sponsored sports activities r =.26, p $<$.01, and volunteering in field-trips r =.28, p $<$.01.^ The multiple regression analysis equation predicting level of homework assistance provided by parents and self-efficacy was statistically significant, F(2,106) = 3.59, p $<$.03. The beta weights revealed that self-efficacy contributed the most to the prediction of homework assistance by parents, B =.258, p $<$.009. In turn, the variable of acculturation was the most significant predictor of number of school based parent involvement activities, B =.281, p $<$.05 level. The path analysis confirmed the results obtained in the multiple regression analyses, establishing self-efficacy as having a direct effect on the level of homework assistance provided by parents. Conversely, the variable of acculturation had a direct effect on the number of school based parent involvement activities. ^

Identification des gènes modifiant l’âge d’apparition du glaucome primaire à angle-ouvert dans une famille canadienne-française fondatrice.

Le glaucome est un groupe hétérogène de maladies qui sont caractérisées par l’apoptose des cellules ganglionnaires de la rétine et la dégénérescence progressive du nerf optique. Il s’agit de la première cause de cécité irréversible, qui touche environ 60 millions de personnes dans le monde. Sa forme la plus commune est le glaucome à angle ouvert (GAO), un trouble polygénique causé principalement par une prédisposition génétique, en interaction avec d’autres facteurs de risque tels que l’âge et la pression intraoculaire élevée (PIO). Le GAO est une maladie génétique complexe, bien que certaines formes sévères sont autosomiques dominantes. Dix-sept loci ont été liés à la maladie et acceptés par la « Human Genome Organisation » (HUGO) et cinq gènes ont été identifiés à ces loci (MYOC, OPTN, WDR36, NTF4, ASB10). Récemment, des études d’association sur l’ensemble du génome ont identifié plus de 20 facteurs de risque fréquents, avec des effets relativement faibles. Depuis plus de 50 ans, notre équipe étudie 749 membres de la grande famille canadienne-française CA où la mutation MYOCK423E cause une forme autosomale dominante de GAO dont l’âge de début est fortement variable. Premièrement, il a été montré que cette variabilité de l’âge de début de l’hypertension intraoculaire possède une importante composante génétique causée par au moins un gène modificateur. Ce modificateur interagit avec la mutation primaire et altère la sévérité du glaucome chez les porteurs de MYOCK423E. Un gène modificateur candidat WDR36 a été génotypé dans 2 grandes familles CA et BV. Les porteurs de variations non-synonymes de WDR36 ainsi que de MYOCK423E de la famille CA ont montré une tendance à développer la maladie plus jeune. Un outil de forage de données a été développé pour représenter des informations connues relatives à la maladie et faciliter la priorisation des gènes candidats. Cet outil a été appliqué avec succès à la dépression bipolaire et au glaucome. La suite du projet consiste à finaliser un balayage de génome sur la famille CA et à séquencer les loci afin d’identifier les variations modificatrices du glaucome. Éventuellement, ces variations permettront d’identifier les individus dont le glaucome risque d’être plus agressif.

Extracting Causal Graphs from an Open Provenance Data Model

The open provenance architecture (OPA) approach to the challenge was distinct in several regards. In particular, it is based on an open, well-defined data model and architecture, allowing different components of the challenge workflow to independently record documentation, and for the workflow to be executed in any environment. Another noticeable feature is that we distinguish between the data recorded about what has occurred, emphprocess documentation, and the emphprovenance of a data item, which is all that caused the data item to be as it is and is obtained as the result of a query over process documentation. This distinction allows us to tailor the system to separately best address the requirements of recording and querying documentation. Other notable features include the explicit recording of causal relationships between both events and data items, an interaction-based world model, intensional definition of data items in queries rather than relying on explicit naming mechanisms, and emphstyling of documentation to support non-functional application requirements such as reducing storage costs or ensuring privacy of data. In this paper we describe how each of these features aid us in answering the challenge provenance queries.

Causal theory for the gauged Thirring model

We consider the (2 + 1)-dimensional massive Thirring model as a gauge theory, with one-fermion flavor, in the framework of the causal perturbation theory and address the problem of dynamical mass generation for the gauge boson. In this context we obtain an unambiguous expression for the coefficient of the induced Chern-Simons term.

Radiative corrections for the gauged Thirring model in causal perturbation theory

We evaluate the one-loop fermion self-energy for the gauged Thirring model in (2+1) dimensions. with one massive fermion flavor. We do this in the framework of the causal perturbation theory. In contrast to QED3, the corresponding two-point function turns out to be infrared finite on the mass shell. Then, by means of a Ward identity, we derive the on-shell vertex correction and discuss the role played by causality for non-renormalizable theories.

Causal amplitudes in the Schwinger model at finite temperature

We show, in the imaginary time formalism, that the temperature dependent parts of all the retarded (advanced) amplitudes vanish in the Schwinger model. We trace this behavior to the CPT invariance of the theory and give a physical interpretation of this result in terms of forward scattering amplitudes of on-shell thermal particles.

B2DI a bayesian BDI agent model with causal belief updating based on MSBN

In this paper, we introduce B2DI model that extends BDI model to perform Bayesian inference under uncertainty. For scalability and flexibility purposes, Multiply Sectioned Bayesian Network (MSBN) technology has been selected and adapted to BDI agent reasoning. A belief update mechanism has been defined for agents, whose belief models are connected by public shared beliefs, and the certainty of these beliefs is updated based on MSBN. The classical BDI agent architecture has been extended in order to manage uncertainty using Bayesian reasoning. The resulting extended model, so-called B2DI, proposes a new control loop. The proposed B2DI model has been evaluated in a network fault diagnosis scenario. The evaluation has compared this model with two previously developed agent models. The evaluation has been carried out with a real testbed diagnosis scenario using JADEX. As a result, the proposed model exhibits significant improvements in the cost and time required to carry out a reliable diagnosis.

Economic performance of Brazilian manufacturing firms: a counterfactual analysis of innovation impacts

This article assesses if innovators outperform non-innovators in Brazilian manufacturing during 1996-2002. To do so, we begin with a simple theoretical model and test the impacts of technological innovation (treatment) on innovating firms (treated) by employing propensity score matching techniques. Correcting for the survivorship bias in the period, it was verified that, on an average, the accomplishment of technological innovations produces positive and significant impacts on the employment, the net revenue, the labor productivity, the capital productivity, and market share of the firms. However, this result was not observed for the mark-up. Especially, the net revenue reflects more robustly the impacts of the innovations. Quantitatively speaking, innovating firms experienced a 10.8-12.5 percentage points (p.p. henceforth) higher growth on employment, a 18.1-21.7 p.p. higher growth on the net revenue, a 10.8-11.9 p.p. higher growth on labor productivity, a 11.8-12.0 p.p. higher growth on capital productivity, and a 19.9-24.3 p.p. higher growth on their market share, relative to the average of the non-innovating firms in the control group. It was also observed that the conjunction of product and process innovations, relative to other forms of innovation, presents the stronger impacts on the performance of Brazilian firms.

Could sudden death syndrome (SDS) in chickens (Gallus gallus) be a valid animal model for sudden unexpected death in epilepsy (SUDEP)?

Epilepsy is the most common serious neurological disorder and approximately 1% of the population worldwide has epilepsy. Moreover, sudden unexpected death in epilepsy (SUDEP) is the most important direct epilepsy-related cause of death. Information concerning fisk factors for SUDEP is conflicting, but potential risk factors include: young age, early onset of epilepsy, duration of epilepsy, uncontrolled seizures, seizure frequency, AED number and winter temperatures. Additionally, the cause of SUDEP is still unknown; however, the most commonly suggested mechanisms are cardiac abnormalities during and between seizures. Similarly, sudden death syndrome (SDS) is a disease characterized by an acute death of well-nourished and seeming healthy Gallus gallus after abrupt and brief flapping of their wings and incidence of SDS these animals has recently increased worldwide. Moreover, the exactly cause of SDS in Gallus gallus is unknown, but is very probable that cardiac abnormalities play a potential role. Due the similarities between SUDEP and SDS and as Gallus gallus behavioral manifestation during SDS phenomenon is close of a tonic-clonic seizure, in this paper we suggest that epilepsy could be a new possible causal factor for SDS. (C) 2009 Elsevier Ltd. All rights reserved.

Decisions with multiple simultaneous goals and uncertain causal effects

A key aspect of decision-making in a disaster response scenario is the capability to evaluate multiple and simultaneously perceived goals. Current competing approaches to build decision-making agents are either mental-state based as BDI, or founded on decision-theoretic models as MDP. The BDI chooses heuristically among several goals and the MDP searches for a policy to achieve a specific goal. In this paper we develop a preferences model to decide among multiple simultaneous goals. We propose a pattern, which follows a decision-theoretic approach, to evaluate the expected causal effects of the observable and non-observable aspects that inform each decision. We focus on yes-or-no (i.e., pursue or ignore a goal) decisions and illustrate the proposal using the RoboCupRescue simulation environment.

On making causal claims: A review and recommendations

Social scientists often estimate models from correlational data, where the independent variable has not been exogenously manipulated; they also make implicit or explicit causal claims based on these models. When can these claims be made? We answer this question by first discussing design and estimation conditions under which model estimates can be interpreted, using the randomized experiment as the gold standard. We show how endogeneity--which includes omitted variables, omitted selection, simultaneity, common methods bias, and measurement error--renders estimates causally uninterpretable. Second, we present methods that allow researchers to test causal claims in situations where randomization is not possible or when causal interpretation is confounded, including fixed-effects panel, sample selection, instrumental variable, regression discontinuity, and difference-in-differences models. Third, we take stock of the methodological rigor with which causal claims are being made in a social sciences discipline by reviewing a representative sample of 110 articles on leadership published in the previous 10 years in top-tier journals. Our key finding is that researchers fail to address at least 66 % and up to 90 % of design and estimation conditions that make causal claims invalid. We conclude by offering 10 suggestions on how to improve non-experimental research.

Causal mechanisms underlying host specificity in bat ectoparasites.

In parasites, host specificity may result either from restricted dispersal capacity or from fixed coevolutionary host-parasite adaptations. Knowledge of those proximal mechanisms leading to particular host specificity is fundamental to understand host-parasite interactions and potential coevolution of parasites and hosts. The relative importance of these two mechanisms was quantified through infection and cross-infection experiments using mites and bats as a model. Monospecific pools of parasitic mites (Spinturnix myoti and S. andegavinus) were subjected either to individual bats belonging to their traditional, native bat host species, or to another substitute host species within the same bat genus (Myotis). The two parasite species reacted differently to these treatments. S. myoti exhibited a clear preference for, and had a higher fitness on, its native host, Myotis myotis. In contrast, S. andegavinus showed no host choice, although its fitness was higher on its native host M. daubentoni. The causal mechanisms mediating host specificity can apparently differ within closely related host-parasite systems.

Autistic spectrum disorder: evaluating a possible contributing or causal role of epilepsy.

The onset of epilepsy in brain systems involved in social communication and/or recognition of emotions can occasionally be the cause of autistic symptoms or may aggravate preexisting autistic symptoms. Knowing that cognitive and/or behavioral abnormalities can be the presenting and sometimes the only symptom of an epileptic disorder or can even be caused by paroxysmal EEG abnormalities without recognized seizures, the possibility that this may apply to autism has given rise to much debate. Epilepsy and/or epileptic EEG abnormalities are frequently associated with autistic disorders in children but this does not necessarily imply that they are the cause; great caution needs to be exercised before drawing any such conclusions. So far, there is no evidence that typical autism can be attributed to an epileptic disorder, even in those children with a history of regression after normal early development. Nevertheless, there are several early epilepsies (late infantile spasms, partial complex epilepsies, epilepsies with CSWS, early forms of Landau-Kleffner syndrome) and with different etiologies (tuberous sclerosis is an important model of these situations) in which a direct relationship between epilepsy and some features of autism may be suspected. In young children who primarily have language regression (and who may have autistic features) without evident cause, and in whom paroxysmal focal EEG abnormalities are also found, the possible direct role of epilepsy can only be evaluated in longitudinal studies.

On making causal claims: A review and recommendations

Social scientists often estimate models from correlational data, where the independent variable has not been exogenously manipulated; they also make implicit or explicit causal claims based on these models. When can these claims be made? We answer this question by first discussing design and estimation conditions under which model estimates can be interpreted, using the randomized experiment as the gold standard. We show how endogeneity--which includes omitted variables, omitted selection, simultaneity, common methods bias, and measurement error--renders estimates causally uninterpretable. Second, we present methods that allow researchers to test causal claims in situations where randomization is not possible or when causal interpretation is confounded, including fixed-effects panel, sample selection, instrumental variable, regression discontinuity, and difference-in-differences models. Third, we take stock of the methodological rigor with which causal claims are being made in a social sciences discipline by reviewing a representative sample of 110 articles on leadership published in the previous 10 years in top-tier journals. Our key finding is that researchers fail to address at least 66 % and up to 90 % of design and estimation conditions that make causal claims invalid. We conclude by offering 10 suggestions on how to improve non-experimental research.

Model-Free Reconstruction of Excitatory Neuronal Connectivity from Calcium Imaging Signals

A systematic assessment of global neural network connectivity through direct electrophysiological assays has remained technically infeasible, even in simpler systems like dissociated neuronal cultures. We introduce an improved algorithmic approach based on Transfer Entropy to reconstruct structural connectivity from network activity monitored through calcium imaging. We focus in this study on the inference of excitatory synaptic links. Based on information theory, our method requires no prior assumptions on the statistics of neuronal firing and neuronal connections. The performance of our algorithm is benchmarked on surrogate time series of calcium fluorescence generated by the simulated dynamics of a network with known ground-truth topology. We find that the functional network topology revealed by Transfer Entropy depends qualitatively on the time-dependent dynamic state of the network (bursting or non-bursting). Thus by conditioning with respect to the global mean activity, we improve the performance of our method. This allows us to focus the analysis to specific dynamical regimes of the network in which the inferred functional connectivity is shaped by monosynaptic excitatory connections, rather than by collective synchrony. Our method can discriminate between actual causal influences between neurons and spurious non-causal correlations due to light scattering artifacts, which inherently affect the quality of fluorescence imaging. Compared to other reconstruction strategies such as cross-correlation or Granger Causality methods, our method based on improved Transfer Entropy is remarkably more accurate. In particular, it provides a good estimation of the excitatory network clustering coefficient, allowing for discrimination between weakly and strongly clustered topologies. Finally, we demonstrate the applicability of our method to analyses of real recordings of in vitro disinhibited cortical cultures where we suggest that excitatory connections are characterized by an elevated level of clustering compared to a random graph (although not extreme) and can be markedly non-local.