Explicit Component Research Articles

What do preservice teachers learn by reflecting upon their emotional experiences during their training? A qualitative approach into four emotions

ABSTRACT Emotions and reflection are critical in teachers’ work. Still, there is no agreement in how these elements connect in assessing past experiences to redesign teaching practices. In this qualitative study, we interviewed six (n = 6) Chilean preservice teachers four times each to analyse what they learn about becoming an educator by reflecting upon four emotions (anger, sadness, pride, and enjoyment). We found that teachers post-hoc reflection upon such emotions provides candidates with information to develop a sense of positional adjustment to overcome emergent difficulties at schools, reach a delimitation between the private and working world, identify teaching enhancement opportunities, and plan the incorporation of strategies in future actions. We also propose a model that coordinates suppressive and generative candidates’ responses after reflecting upon their emotions. In addition, candidates perceive themselves to be unequipped to deal with their own and external emotions effectively. We suggest that emotional training should be considered as an explicit component of teacher education in Latin America.

Human-Mosquito Contact: A Missing Link in Our Understanding of Mosquito-Borne Disease Transmission Dynamics.

Despite the critical role that contact between hosts and vectors, through vector bites, plays in driving vector-borne disease (VBD) transmission, transmission risk is primarily studied through the lens of vector density and overlooks host–vector contact dynamics. This review article synthesizes current knowledge of host–vector contact with an emphasis on mosquito bites. It provides a framework including biological and mathematical definitions of host–mosquito contact rate, blood-feeding rate, and per capita biting rates. We describe how contact rates vary and how this variation is influenced by mosquito and vertebrate factors. Our framework challenges a classic assumption that mosquitoes bite at a fixed rate determined by the duration of their gonotrophic cycle. We explore alternative ecological assumptions based on the functional response, blood index, forage ratio, and ideal free distribution within a mechanistic host–vector contact model. We highlight that host–vector contact is a critical parameter that integrates many factors driving disease transmission. A renewed focus on contact dynamics between hosts and vectors will contribute new insights into the mechanisms behind VBD spread and emergence that are sorely lacking. Given the framework for including contact rates as an explicit component of mathematical models of VBD, as well as different methods to study contact rates empirically to move the field forward, researchers should explicitly test contact rate models with empirical studies. Such integrative studies promise to enhance understanding of extrinsic and intrinsic factors affecting host–vector contact rates and thus are critical to understand both the mechanisms driving VBD emergence and guiding their prevention and control.

Conformal Lagrangians from the (formal) near boundary analysis of AdS gauge fields

A simple generating procedure for Lagrangians of conformal gauge fields of mixed-symmetry type is presented. The construction originates from the analysis of the near-boundary behaviour of the associated AdS gauge fields using the ambient space approach to leading boundary values. Manifestly ambient form of the Lagrangian is also obtained. As an illustration we apply the procedure to the simplest mixed-symmetry conformal gauge field, described by the two-row Young diagram, and derive the explicit component form of the respective Lagrangian.

Considering Situational Variety in Contextualized Aging Research - Opinion About Methodological Perspectives.

Due to the increasingly heterogeneous trajectories of aging, gerontology requires theoretical models and empirical methods that can meaningfully, reliably, and precisely describe, explain, and predict causes and effects within the aging process, considering particular contexts and situations. Human behavior occurs in contexts; nevertheless, situational changes are often neglected in context-based behavior research. This article follows the tradition of environmental gerontology research based on Lawton’s Person-Environment-Interaction model (P-E model) and the theoretical developments of recent years. The authors discuss that, despite an explicit time component, current P-E models could be strengthened by focusing on detecting P-E interactions in various everyday situations. Enhancing Lawton’s original formula via a situationally based component not only changes the theoretical perspectives on the interplay between person and environment but also demands new data collection approaches in empirical environmental research. Those approaches are discussed through the example of collecting mobile data with smartphones. Future research should include the situational dimension to investigate the complex nature of person environment interactions.

Speech auditory-motor adaptation to formant-shifted feedback lacks an explicit component: Reduced adaptation in adults who stutter reflects limitations in implicit sensorimotor learning.

The neural mechanisms underlying stuttering remain poorly understood. A large body of work has focused on sensorimotor integration difficulties in individuals who stutter, including recently the capacity for sensorimotor learning. Typically, sensorimotor learning is assessed with adaptation paradigms in which one or more sensory feedback modalities are experimentally perturbed in real time. Our own previous work on speech with perturbed auditory feedback revealed substantial auditory-motor learning limitations in both children and adults who stutter (AWS). It remains unknown, however, which subprocesses of sensorimotor learning are impaired. Indeed, new insights from research on upper limb motor control indicate that sensorimotor learning involves at least two distinct components: (a) an explicit component that includes intentional strategy use and presumably is driven by target error and (b) an implicit component that updates an internal model without awareness of the learner and presumably is driven by sensory prediction error. Here, we attempted to dissociate these components for speech auditory-motor learning in AWS versus adults who do not stutter (AWNS). Our formant-shift auditory-motor adaptation results replicated previous findings that such sensorimotor learning is limited in AWS. Novel findings are that neither control nor stuttering participants reported any awareness of changing their productions in response to the auditory perturbation and that neither group showed systematic drift in auditory target judgments made throughout the adaptation task. These results indicate that speech auditory-motor adaptation to formant-shifted feedback relies exclusively on implicit learning processes. Thus, limited adaptation in AWS reflects poor implicit sensorimotor learning. Speech auditory-motor adaptation to formant-shifted feedback lacks an explicit component: Reduced adaptation in adults who stutter reflects limitations in implicit sensorimotor learning.

Flappy Bird Automation using TensorFlow

Playing computer games has made a noteworthy changeover to our age's playing style by making the more significant part of them to stick to it. In this way, tackling those diversion issues is a fascinating subject that requires cautious area explicit component definition and an adaptable amusement hypothesis look calculation. So, in this manner, we picked an amusement flappy feathered creature, which includes exploring a winged animal through a bundle of obstacles (pipes) and influence it to make due for quite a while in a steady progression. In addressing this issue, we employed the use of such RL (reinforcing learning) by defining the correct component and after that through the proper activities at every amusement occasion, contributes the pre-emptive specialist who has gotten from a model of CNN (convolutional neural system) which acts as a decent defining product while removing elements from their previous feed previews. We extend a general framework to learn essential highlights of diversion and deal with the problem as appropriate.

A non-parametric framework to estimate fertilization response in loblolly pine plantations using environmental covariates

Abstract Fertilization is a common practice to increase the productivity and the stand value in the southeastern US. The decision to fertilize a given site is driven by site characteristics and the expected magnitude of response. To determine the magnitude, forest researchers typically rely on fertilization trials established throughout the region of interest and derive growth equations to reflect an increase in either site index or volume. Such equations lack an explicit spatial prediction component. To bridge this gap, we developed a modeling framework that explicitly evaluates the likelihood of a fertilization response as a binary process and the magnitude of such response as a separate model. The methodology relies on the non-parametric interpolator thin plate spines. To test the efficacy of this framework, both percent volume and dominant height response to repeated fertilizer treatments were estimated using data from long-term research trials in Georgia. Several environmental covariates were evaluated on their ability to reduce the models’ root mean square error and account for more of the variation in percent gain from fertilization regimes. Results showed that the inclusion of such covariates improved the model performance and reduced errors associated with interpolation. Thresholding expected responses from fertilization treatments allows practitioners to evaluate the probability of achieving a given response.

Distraction in Visual Working Memory: Resistance is Not Futile.

Over half a century of research focused on understanding how working memory is capacity constrained has overshadowed the fact that it is also remarkably resistant to interference. Protecting goal-relevant information from distraction is a cornerstone of cognitive function that involves a multifaceted collection of control processes and storage mechanisms. Here, we discuss recent advances in cognitive psychology and neuroscience that have produced new insights into the nature of visual working memory and its ability to resist distraction. We propose that distraction resistance should be an explicit component in any model of working memory and that understanding its behavioral and neural correlates is essential for building a comprehensive understanding of real-world memory function.

Guided Attention Inference Network.

With only coarse labels, weakly supervised learning typically uses top-down attention maps generated by back-propagating gradients as priors for tasks such as object localization and semantic segmentation. While these attention maps are intuitive and informative explanations of deep neural network, there is no effective mechanism to manipulate the network attention during learning process. In this paper, we address three shortcomings of previous approaches in modeling such attention maps in one common framework. First, we make attention maps a natural and explicit component in the training pipeline such that they are end-to-end trainable. Moreover, we provide self-guidance directly on these maps by exploring supervision from the network itself to improve them towards specific target tasks. Lastly, we proposed a design to seamlessly bridge the gap between using weak and extra supervision if available. Despite its simplicity, experiments on the semantic segmentation task demonstrate the effectiveness of our methods. Besides, the proposed framework provides a way not only explaining the focus of the learner but also feeding back with direct guidance towards specific tasks. Under mild assumptions our method can also be understood as a plug-in to existing convolutional neural networks to improve their generalization performance.

Moral Self-Reflection and Leaders’ Virtuous Behaviors

Self-reflection, defined as the extent to which a person inspects and evaluates his/her thoughts, feelings, and behaviors, has been considered as part of self-consciousness in philosophy and the psychological self-regulation literature. We seek to extend the knowledge on self-reflection and behavioral ethics by adding an explicit moral component to self-reflection and by examining its effect on the leaders’ virtuous behavior. Building on the conceptions of moral self-reflection in Confucian and Western psychological research, we propose that moral self-reflection consists of self-introspection on the morality of intentions, habits, and the adherence to community norms. We further propose that moral self-reflection increases the leaders’ humble behaviors and ethical leadership but inhibits abusive supervision by providing other-oriented cognition (leader other-benefiting accountability). We use a mixed design of qualitative and quantitative studies for testing the theoretical model, which consists of 1) professional and manager interviews to generate items of moral self-reflection, 2) exploratory and confirmatory factor analyses to validate the moral self-reflection measure, and 3) a field study of managers and their subordinates.

The relationship between education, agency, and socialization goals in a sample of mothers of preschoolers

ABSTRACT The Ecocultural Model of Development states that parents’ cultural model mediates the relationship between their educational level and their socialization goals. Cultural models refer to beliefs shared by members of a community, and they result from the combination of two dimensions: agency and interpersonal distance. Moreover, both agency and interpersonal distance are made up of explicit and implicit components. In the present study, we focused on how the explicit and the implicit components of the agency dimension of the cultural model are related to mothers’ educational level and socialization goals. The results on this sample (N = 141) suggest that there was a significant indirect effect of mothers’ educational level on their heteronomous socialization goals through the implicit component of the agency dimension, namely attributional style. The higher the mothers’ educational level, the more they attributed other individuals’ behaviour internally and the less they valued socialization goals focused on heteronomy. Moreover, the results suggest that the implicit component of agency is related to mothers’ socialization goals, while the explicit component is not. This is in concordance with research showing that the implicit components of individuals’ cultural model can be better used to differentiate between individuals from different cultures.

Why is the explicit component of motor adaptation limited in elderly adults?

The cognitive component of motor adaptation declines with aging. Yet, in other motor tasks, older adults appear to rely on cognition to improve their motor performance. It is unknown why older adults are not able to do so in motor adaptation. To solve this apparent contradiction, we tested the possibility that older adults require more cognitive resources in unperturbed reaching compared with younger adults, which leaves fewer resources available for the cognitive aspect of motor adaptation. Two cognitive-motor dual-task experiments were designed to test this. The cognitive load of unperturbed reaching was assessed via dual-task costs during the baseline period of visuomotor rotation experiments, which provided us with an estimation of the amount of cognitive resources used during unperturbed reaching. However, we did not observe a link between dual-task costs and explicit adaptation in both experiments and, therefore, failed to confirm this hypothesis. Instead, we observed that explicit adaptation was mainly associated with visuospatial working memory capacity. This suggests that visuospatial working memory of an individual might be linked to the extent of explicit adaptation for young and older adults.NEW & NOTEWORTHY Our work addresses the contradiction between the age-related increase in the contribution of cognition for the execution of motor tasks and the age-related decrease in the cognitive component of motor adaptation. We predicted that elderly adults would need more cognitive resources for reaches and would, therefore, not have enough cognitive resources available for adaptation. Rather, we observed that visuospatial abilities could better explain the amount of cognition used by our participants for motor adaptation.

Consolidation and retention of motor skill after motor imagery training

Complex motor tasks are learned through training which results in lasting improvement in sensorimotor performance and accuracy. Learning a motor skill is commonly attained via physical execution. However, research has shown that cognitive training, such as motor imagery (MI), effectively facilitates skill learning. Neurophysiological findings suggest that learning-induced plasticity in the human motor cortex, subserving consolidation and retention of motor skills, is stronger after movement execution (ME) than after MI training. Here, we designed an experimental task able to test for the fast and slow learning phases and for retention of motor skills for both MI and ME. We hypothesize that differences between MI and ME training would emerge in terms of reduced consolidation and retention of motor skills. Twenty-four young healthy subjects were divided into two groups, performing MI or ME training. Participants wore sensor-engineered gloves and their sensorimotor performance was assessed over a period of 15 days with 4-days training. We analysed the touch duration (TD), the inter-tapping interval (ITI), movement rate and accuracy. Results showed that (i) during the first phase of acquisition of motor skills, sensorimotor performance improved similarly in MI and ME groups; (ii) during the second learning phase movement rate increased more in ME than MI group and this difference was mainly driven by differences in the duration of TD; (iii) consolidation deficits with MI training reflected in impaired retention of the acquired skills, as TD and ITI were larger and movement rate was lower in the MI group with respect to the ME, till to 10 days after the last training session. Explicit component of motor learning, accuracy, was maintained in retention phase in both groups. Following our hypothesis, our findings show that MI training is as effective as ME within the first learning phase, but consolidation and retention of motor skills are less effective following MI training. This study highlights MI limitations and suggests option to enhance MI, as by providing an external sensory feedback.

Generalized and Variational Statements of the Riemann Problem with Applications to the Development of Godunov’s Method

This paper is devoted to the numerical method for solving the fluid dynamics equations proposed by Godunov more than 60 years ago. This method is an explicit finite volume first-order discretization of the system of balance differential equations with the approximation of the numerical flux on the faces of the computational cells based on the exact solution of the Riemann problem. Statements of the generalized and variational Riemann problem are considered, and it is shown how the solutions to these problems can be used for the development of Godunov’s method. In particular, the issues of increasing the order of approximation, constructing an implicit–explicit stable temporal scheme that is reduced to the second-order Godunov scheme when only the purely explicit component is used, solving discrete equations of the implicit–explicit scheme using the solution to the variational Riemann problem, and a generalization of Godunov’s method for the linearized system of Euler equations are considered. Approximate solutions to the generalized Riemann problem that are analogs of the HLL and HLLC solutions for the case of linear initial data are obtained.

Граматичні особливості ідеостилю Лесі Українки: функції локатива у драмі-феєрії «Лісова пісня»

The article deals with the analysis of the grammatical features of Lesya Ukrainka’s individual style. In the focus is the identification of the locative functions in the fairy-drama “The Forest Song”. Locative is defined as a component of the semantic-syntactic structure of a sentence, dependent on a verbal predicate that expresses varieties of spatial meaning. The article argues the notion of syntactic dependency applicability in the analysis of a sentence structure. The study has revealed that the predicates expressing the locative dependency have the correlated semantics in sentence constructions. In the semantic-syntactic structure of sentence constructions, predicates of static semantics, predicates of process, and predicates of action determine the locative’s components. The author lays emphasis on the semantic meanings of the locative's components. They are dependent on the predicates of static semantics, predicates of process, and predicates of action. In the sentence structures of the fairy-drama The Forest Song, most locatives' components express static location, the starting point of movement, a path of movement, and the destination point. The semantic special features of syntactic units represent Lesya Ukrainka’s holistic worldview, indicate her individual style. The locative reflects the world around represented in spatial nominations. The explicit locative component has been recorded in the sentence constructions with predicates of static semantics as well as there are elliptical sentences with the implicit predicate of static semantics. The predicates of process and action predetermine explicit and implicit locative components. It was found that the locative is mainly represented by prepositional case forms. It turns out that the distinctive feature of all sentences with locative components is presence of prepositions as markers of locative dependency. The locative components are presented in two-member and one-member sentences, in elliptical and imperative sentence constructions.

\u201cEthics When You Least Expect It\u201d: A Modular Approach to Short Course Data Ethics Instruction

Data science skills are rapidly becoming a necessity in modern science. In response to this need, institutions and organizations around the world are developing research data science curricula to teach the programming and computational skills that are needed to build and maintain data infrastructures and maximize the use of available data. To date, however, few of these courses have included an explicit ethics component, and developing such components can be challenging. This paper describes a novel approach to teaching data ethics on short courses developed for the CODATA-RDA Schools for Research Data Science. The ethics content of these schools is centred on the concept of open and responsible (data) science citizenship that draws on virtue ethics to promote ethics of practice. Despite having little formal teaching time, this concept of citizenship is made central to the course by distributing ethics content across technical modules. Ethics instruction consists of a wide range of techniques, including stand-alone lectures, group discussions and mini-exercises linked to technical modules. This multi-level approach enables students to develop an understanding both of “responsible and open (data) science citizenship”, and of how such responsibilities are implemented in daily research practices within their home environment. This approach successfully locates ethics within daily data science practice, and allows students to see how small actions build into larger ethical concerns. This emphasises that ethics are not something “removed from daily research” or the remit of data generators/end users, but rather are a vital concern for all data scientists.

Concurrent and Longitudinal Contributions of a Brief Assessment of Reading‐Specific Executive Function to Reading Comprehension in First and Second Grade Students

ABSTRACTExecutive function (EF) contributes significantly to reading comprehension across the lifespan. Emerging research indicates domain‐specific assessments of EF are better suited for assessment and intervention in academic contexts. For example, graphophonological‐semantic cognitive flexibility (GSF), the ability to flexibly switch between the graphophonological and semantic components of printed words, contributes uniquely to reading comprehension across the lifespan, and GSF training improves children's reading comprehension. This study compared the original GSF measure, which is problematic for use in schools due to its subjectively interpreted explicit explanation component, to an abbreviated implicit task that is better suited for assessment of GSF in practical contexts in 68 first and second grade students. Implicit and explicit GSF contributed uniquely to reading comprehension concurrently and longitudinally when children (n = 31) were in third and fourth grades, beyond verbal ability, decoding ability, and matrix reasoning.

Cyber-Physical Trust Systems Driven by Blockchain

Cyber Physical Trust Systems (CPTS) are Cyber Physical Systems and Internet of Things enriched with trust as an explicit, measurable, testable and verifiable system component. In this paper, we propose to use blockchain, a distributed ledger technology, as the trust enabling system component for CPTS. We propose two schemes for CPTSs driven by blockchain in relation to two typical network model cases. We show that our proposed approach achieves the security properties, such as device identification, authentication, integrity, and non-repudiation, and provides protection against popular attacks, such as replay and spoofing. We provide formal proofs of those properties using the Tamarin Prover tool. We describe results of a proof-of-concept which implements a CPTS driven by blockchain for physical asset management and present a performance analysis of our implementation. We identify use cases in which CPTSs driven by blockchain find applications.

Biotope Area Factor: An Ecological Urban Index to Geovisualize Soil Sealing in Padua, Italy

Over the last few years, soil sealing has been recognized as one of the major threats in terms of soil degradation and loss of ecosystem services. Although many efforts have been promoted to increase the awareness of safeguarding soil for stakeholders, its value as a non-renewable resource as well as soil-related services in urban ecosystems is not implemented enough in urban planning and policies. Due to the spatially explicit component and the geographical scale of soil sealing, mapping and quantifying the number of sealed surfaces is crucial. The aim of this paper was to estimate and geovisualize the soil sealed in the city of Padua (Italy) at a very detailed scale, testing the use of the Biotope Area Factor (BAF) index. Moreover, the paper aimed to simulate an alternative mitigation scenario in a specific study area of the city. Spatial analysis was performed testing the BAF index in a Geographic Information Sistem (GIS) environment and using aerial ortho-photos at very high resolution. The results show different values of the BAF index for all four neighborhoods from 0.35 to 0.69. In the mitigation scenario, the value of the BAF index was improved using a measure of green roofs. In conclusion, the paper provides an insightful case study for enriching the debate about soil sealing and gives scientific support for sustainable urban planning.

Treatment of the implicit effect in Shark-X

Shark-X is a set of Perl-based tools build around the deterministic neutron transport code CASMO-5, used to perform uncertainty quantification for lattice calculations at the Paul Scherrer Institut (PSI). While perturbing an input parameter, e.g. a cross section in a given energy range, the resulting perturbation to the effective cross section, e.g. multigroup cross section, can be expressed as the sum of an explicit and implicit component. The implicit term stems from changes in the neutron flux resulting from the cross section perturbation. This effect is neglected when using the standard perturbation theory methodology, even though its importance for uncertainty quantification is reported in the literature.The objectives of the paper are, in view of further enhancing Shark-X, to review a set of existing methods and to propose novel methodologies in order to accurately take the implicit effect into account in the resonance shielding treatment of CASMO-5; as well as to assess the importance of the new tool for typical LWR applications.Amongst the methods considered, those based on an equivalence in dilution allow perturbing the group-averaged cross sections without having to solve the slowing down problem in conjunction with the perturbed point-wise cross sections. However, such methods are found to show only limited improvements as compared to the standard perturbed self-shielded cross sections determined neglecting the implicit effect. As a result, a simpler approach based on the pre-determination of perturbation factors is adopted and implemented into Shark-X and CASMO-5. The new implementation is successfully tested and verified by comparing k-inf sensitivity coefficients computed with Shark-X with those from a Monte-Carlo reference solution, and this for a range of simple homogeneous mixtures as well as for LWR pin cells and lattices.Finally, the paper demonstrates through simple considerations, that the magnitude of the implicit effect is related to the energy group structure in the resolved resonance region, which might be specific to the code used to compute the sensitivity coefficients. The finer is the energy mesh; the smaller is also the impact of the implicit effect, and as such the necessity for a specific treatment.